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  • Best AI for OCT: 10 Essential Features Your Platform Must Have 

    best AI for OCT
    Maria Martynova
    8 min.

    Best AI for OCT: 10 Essential Features Your Platform Must Have 

    So you’ve decided to trial AI for OCT analysis and wondering how to choose among all the available platforms. To save you some time, we’ve collected 10 most essential criteria according to which you can assess all existing AI platforms. Using this criteria you will be able to make an informed and rational choice.

    As an ophthalmologist, I am interested in finding innovative and modern approaches that could help me to enhance the workflow and improve patient outcome as a result.Analyzing various platforms, I realized that these 10 criteria are crucial for the right choice.

    1. Regulatory Compliance and Clinical Validation

    In healthcare, safety is always first. Regulatory approval and clinical validation are essential for AI-powered platforms for OCT scan analysis.

    The best AI OCT platforms should meet regulatory standards set by authorities such as the FDA, HIPAA, CE, and ISO. 

    Adhering to regulatory guidelines enhances credibility and fosters trust among healthcare professionals. Check if the AI for OCT analysis tool has all these certificates in place and if they are valid.

    FDA-cleared AI for OCT analysis

    Trial AI for OCT or learn more about it

    Demo Account Get brochure

     

    2.Wide range of biomarkers and pathologies detected

    Some AI for OCT platforms concentrate on certain pathologies, like  Age-Related Macular Degeneration (AMD) or Diabetic Retinopathy, because of the prevalence of these conditions among the population. It mostly means that eye care specialists must know in advance that they are dealing with the AMD patient to find the proof of AMD on the OCT.

    The best AI for OCT tools should have a wide variety of biomarkers and pathologies, including rare ones that cannot be seen daily in clinical practice, such as central retinal vein and artery occlusions, vitelliform dystrophy, macular telangiectasia and others. Altris AI, the leader of OCT for AI analysis, detects 74 biomarkers and pathologies as of today. 

    best AI for OCT

    3.Cloud-Based Data Management and Accessibility

    To ensure seamless integration into clinical workflows, the AI OCT platform should offer cloud-based data management and accessibility. Cloud storage allows for easy retrieval of patient records, remote consultations, and multi-location access. Secure cloud computing also enhances collaboration between ophthalmologists, optometrists, and researchers by enabling data sharing while maintaining compliance with data privacy regulations such as HIPAA and GDPR. 

    Many clinics have strict policies regarding patient data storage as well: it is crucial that the data is stored on the servers in the region of operation. If the clinic is in EU, the data should be stored in the EU.

    4.Real-world usage by eye care specialists

    When choosing the best AI for OCT analysis, real-world usage by eye care specialists is the most critical factor. Advanced algorithms and high accuracy metrics mean little if the AI is not seamlessly integrated into clinical workflows and actively used by optometrists and ophthalmologists. There are thousands of research models available, but when it comes to the implementation, most of them are not available to ECPs.

    Eye care professionals are not IT specialists. They require AI that is intuitive, fast, and reliable. If a system disrupts their workflow, generates excessive false alerts, or lacks clear explanations for its findings, adoption rates will be low—even if the technology itself is powerful. The best AI solutions are those that specialists trust and rely on daily to enhance diagnostic accuracy, streamline patient management, and support decision-making.

    Moreover, real usage generates valuable feedback that continuously improves the AI. Systems actively used in clinical settings undergo rapid validation, refinement, and adaptation to diverse patient populations. This real-world data is far more meaningful than isolated test results in controlled environments.

    5. Customizable Reporting and Visualization Tools

    Reports are the result of the whole AI for OCT scan analysis that is why customizable and comprehensive reports are a must.

    A high-quality AI OCT platform must offer customizable reporting and visualization tools. Clinicians should be able to adjust parameters, select specific data points, and generate detailed reports tailored to individual patient needs.

    Heatmaps, 3D reconstructions, and trend analysis graphs should be available to help visualize disease progression. These tools improve the interpretability of AI-generated insights and facilitate patient education.

    FDA-cleared AI for OCT analysis

    Trial AI for OCT or learn more about it

    Demo Account Get brochure

     

    6.AI for Early Glaucoma Detection

    Glaucoma is a leading cause of irreversible blindness, and since OCT is widely used to assess the retinal nerve fiber layer (RNFL), Ganglion Cell Complex ( GCC), optic nerve head (ONH), AI can significantly enhance early detection and risk assessment.

    Therefore, the best AI for OCT analysis tools have an AI for early glaucoma detection module available to assess the risk of glaucoma especially at the early stage. Moreover, tracking the progression of glaucoma with the help of AI should also be available for eye care specialists.  

    Clear and bright notifications about glaucoma risk are also vital for making AI glaucoma modules easy to use.  AI can provide proactive insights that enable early intervention and personalized treatment plans

    AI to detect glaucoma

    7.User – Friendly Interface and Intuitive Workflow Integration

    A well-designed AI OCT platform should feature a user-friendly interface that integrates seamlessly into existing clinical workflows. 

    It means that even non-tech-savvy eye care specialists should be able to navigate it effortlessly. 

    The interface should be intuitive, reducing the learning curve for healthcare providers. Features such as automated scan interpretation, voice command functionality, and guided step-by-step analysis can enhance usability and efficiency.

    8.Integration with Electronic Health Records (EHRs)

    For a seamless clinical experience, the AI OCT platform should integrate with existing electronic health record (EHR) systems. Automated data synchronization between AI analysis and patient records enhances workflow efficiency and reduces administrative burden. This feature enables real-time updates, streamlined documentation, and easy access to past diagnostic reports.

    9. Universal AI solutions compatible with all OCT devices

    Uf you want to use AI to analyze OCT, this AI should be trained on data received from various OCT devices and therefore should be applicable with various OCT devices. A vendor-neutral AI tool for OCT analysis provides unmatched advantages over proprietary solutions tied to specific hardware. By working seamlessly with multiple OCT devices, it eliminates the need for costly equipment upgrades and ensures broader accessibility across clinics and hospitals.

    This approach also fosters greater innovation, allowing AI models to continuously improve based on diverse datasets rather than being limited to a single manufacturer’s ecosystem. Vendor-neutral solutions integrate effortlessly into existing workflows, reducing training time and boosting efficiency. Clinicians benefit from unbiased, adaptable technology that prioritizes patient outcomes rather than locking users into restrictive ecosystems.

    10. Cost-Effectiveness and Accessibility

    To maximize its impact, an AI-powered OCT platform should be cost-effective and accessible to a wide range of healthcare providers. Affordable pricing models, including subscription-based or pay-per-use plans, can make AI technology available to smaller clinics and developing regions. Accessibility ensures that AI-driven OCT analysis benefits as many patients as possible, improving global eye health outcomes.

    FDA-cleared AI for OCT analysis

    Trial AI for OCT or learn more about it

    Demo Account Get brochure

    Conclusion

    What is the best  AI for OCT scan analysis? The best AI for OCT must be a comprehensive, intelligent, and adaptable platform that enhances diagnostic accuracy, streamlines clinical workflows, and supports proactive eye care. Key features such as high-accuracy automated analysis, multi-modal imaging integration, real-time decision support, cloud-based data management, interoperability, and explainable AI decision-making are crucial for an effective OCT AI system. By incorporating these attributes, AI-driven OCT platforms can revolutionize ophthalmology, enabling early disease detection, personalized treatment planning, and improved patient outcomes. As AI technology continues to advance, its integration with OCT will play an increasingly vital role in shaping the future of eye care.

     

  • Future of Ophthalmology: 2025 Top Trends

    future of ophthalmology
    Maria Znamenska
    13.03.2025
    12 min read

    Future of Ophthalmology: 2025 Top Trends

    In a recent survey conducted by our team, we asked eye care specialists to identify the most transformative trends in ophthalmology by 2025. The results highlighted several key areas, with artificial intelligence (AI) emerging as the clear frontrunner, cited by 78% of respondents.

    future of Ophthalmology

    However, the survey also underscored the significant impact of optogenetics, novel AMD/GA therapies, and the continuing evolution of anti-VEGF treatments. This article will explore the practical implications of these advancements, providing an overview of how they are poised to reshape diagnosis, treatment, research, and, ultimately, patient outcomes in ophthalmology.

    FDA-cleared AI for OCT analysis

    Demo Account Get brochure

     

    Building upon the survey’s findings, we begin with the most prevalent trend:

    AI in Ophthalmology

    future of opthalmology

    AI in Clinical Eye Care Practice

    With the increasing prevalence of conditions like diabetic retinopathy and age-related macular degeneration, there is a growing need for efficient and accurate screening tools. And AI is already valuable for eye-care screening: algorithms can analyze retinal images and OCT scans to identify signs of these diseases, enabling early detection and timely intervention.

    future of ophthalmology

    Source

    AI-powered screening tools can also help identify rare inherited retinal dystrophies, such as Vitelliform dystrophy and Macular telangiectasia type 2. These conditions can be challenging to diagnose, but AI algorithms can analyze retinal images to detect subtle signs that human observers may miss.

    future of ophthalmology

    Biomarkers of MacTel 2 detected and visualized by AI for OCT platform, Altris AI

    AI also starts to play a crucial role in glaucoma management. Early detection of glaucoma demands exceptional precision, as the early signs are often subtle and difficult to detect. Another significant challenge in glaucoma screening is the high rate of false positive referrals, which can lead to unnecessary appointments in secondary care and cause anxiety for patients—yet delayed or missed detection of glaucoma results in irreversible vision loss for millions of people worldwide. So, automated AI-powered glaucoma analysis can offer transformative potential to improve patient outcomes.

    One example of promising AI technology is Altris AI, artificial intelligence for OCT scan analysis, which has introduced its Advanced Optic Disc (OD) Analysis that provides a comprehensive picture of the optic disc’s structural damage, allowing detailed glaucoma assessment for treatment choice and monitoring.

    AI for Glaucoma Detection

    This OD module evaluates optic disc parameters using OCT, providing personalized assessments by accounting for individual disc sizes and angle of rim absence. Such a tailored approach eliminates reliance on normative databases, making evaluations more accurate and patient-specific.

    Furthermore, it enables cross-evaluation across different OCT systems, allowing practitioners to analyze macula and optic disc pathology, even when data originates from multiple OCT devices. Key parameters evaluated by Altris AI’s Optic Disc Analysis include disc area, cup area, cup volume, minimal and maximum cup depth, cup/disc area ratio, rim absence angle, and disc damage likelihood scale (DDLS).

    future of ophthalmology

     

    AI for Clinical Trials and Research

    AI is revolutionizing clinical trials and research in ophthalmology. One such key application of AI is biomarker discovery and analysis. Algorithms can analyze large datasets of medical images, such as OCT scans, to identify and quantify biomarkers for various eye diseases. These biomarkers can be used to assess disease progression, monitor treatment response, and predict clinical outcomes.

    AI is also being used to improve the efficiency and effectiveness of clinical trials. By automating the process of identifying eligible patients for clinical trials, AI can help researchers recruit participants more quickly and ensure that trials include appropriate patient populations, accelerating the development of new treatments.

    future of ophthalmology

    Algorithms can analyze real-world data (RWD) collected from electronic health records and other sources to generate real-world evidence (RWE). RWE provides valuable insights into disease progression, treatment patterns, and long-term outcomes in everyday clinical settings, complementing the findings of traditional randomized controlled trials.

    Oculomics

    Integrating digitized big data and computational power in multimodal imaging techniques has presented a unique opportunity to characterize macroscopic and microscopic ophthalmic features associated with health and disease, a field known as oculomics. To date, early detection of dementia and prognostic evaluation of cerebrovascular disease based on oculomics has been realized. Exploiting ophthalmic imaging in this way provides insights beyond traditional ocular observations.

    future of ophthalmology

    For example, the NeurEYE research program, led by the University of Edinburgh, is using AI to analyze millions of anonymized eye scans to identify biomarkers for Alzheimer’s disease and other neurodegenerative conditions. This research can potentially revolutionize early detection and intervention for these devastating diseases.

    Another effort spearheaded by researchers from Penn Medicine, Penn Engineering is exploring the use of AI to analyze retinal images for biomarkers indicative of cardiovascular risk. AI systems are being trained on fundus photography to detect crucial indicators, such as elevated HbA1c levels, a hallmark of high blood sugar, and a significant risk factor for both diabetes and cardiovascular diseases.

    future of ophthalmology

    Source

    AI analysis of retinal characteristics, such as retinal thinning, vascularity reduction, corneal nerve fiber damage, and eye movement, has shown promise in predicting Neurodegenerative diseases. Specifically, decreases in retinal vascular fractal dimension and vascular density have been identified as potential biomarkers for early cognitive impairment, while reductions in the retinal arteriole-to-venular ratio correlate with later stages.

    Moving from AI, we now turn to another significant trend identified in our survey:

    Optogenetics

    Optogenetics represents a significant leap forward in ophthalmic therapeutics, offering a potential solution for vision restoration in patients with advanced retinal degenerative diseases, where traditional gene therapy often falls short. While gene replacement therapies are constrained by the need for viable target cells and the complexity of multi-gene disorders like retinitis pigmentosa (RP), optogenetics offers a broader approach.

    future of ophthalmology

    This technique aims to circumvent the loss of photoreceptors by introducing light-sensitive proteins, known as opsins, into the surviving inner retinal cells and optic nerve, restoring visual function through light modulation. This method is particularly advantageous as it is agnostic to the specific genetic cause of retinal degeneration.

    By delivering opsin genes to retinal neurons, the technology enables the precise manipulation of cellular activity, essentially transforming these cells into new light-sensing units. This approach can bypass the damaged photoreceptor layer, transmitting visual signals directly to the brain.

    Several companies are pioneering advancements in this field. RhyGaze, for example, has secured substantial funding to accelerate the development of its lead clinical candidate, a novel gene therapy designed for optogenetic vision restoration. Their efforts encompass preclinical testing, including pharmacology and toxicology studies, an observational study to define clinical endpoints, and a first-in-human trial to assess safety and efficacy. The success of RhyGaze’s research could pave the way for widespread clinical applications, significantly impacting the treatment of blindness globally.

    future of ophthalmology

    Source

    Nanoscope Therapeutics is also making significant strides with its MCO-010 therapy. This investigational treatment, administered through a single intravitreal injection, delivers the Multi-Characteristic Opsin (MCO) gene, enabling remaining retinal cells to function as new light-sensing cells. Unlike earlier optogenetic therapies that required bulky external devices, MCO-010 eliminates the need for high-tech goggles, simplifying the treatment process and enhancing patient convenience. The ability to restore light sensitivity without external devices represents a major advancement, potentially broadening the applicability of optogenetics to a wider patient population.

    future of ophthalmology

    Source

    Another critical area of innovation highlighted in our survey is the advancement of treatments for AMD and GA.

    New AMD/GA Treatment

    Age-related macular degeneration (AMD) and geographic atrophy (GA) represent a significant challenge in ophthalmology, demanding innovative therapeutic strategies beyond the established anti-VEGF paradigm.

    future of ophthalmology

    Source

    Gene Correction

    Gene editing is emerging as a powerful tool in the fight against AMD and GA, potentially correcting the underlying genetic errors that contribute to these diseases. Essentially, it allows us to make precise changes to a patient’s DNA.

    Traditional gene editing techniques often rely on creating ‘double-strand breaks’ (DSBs) in the DNA at specific target sites, which are like precise cuts in the DNA strand. These cuts are made using specialized enzymes, like CRISPR-Cas9, which act as molecular scissors. While effective, these methods can sometimes introduce unwanted changes at the cut site, such as small insertions or deletions.

    After a DSB is made, the cell’s natural repair mechanisms kick in. There are two main pathways:

    • Non-Homologous End Joining (NHEJ): This is the cell’s quick-fix method. It essentially glues the broken ends back together. However, this process can sometimes introduce errors, leading to small insertions or deletions that can disrupt the gene’s function.
    • Homology-Directed Repair (HDR): This is a more precise repair method. It uses a ‘donor’ DNA template to guide the repair process, ensuring accuracy. However, HDR is more complex and less efficient, especially in non-dividing cells.

    To overcome these limitations of traditional gene editing, researchers have developed more precise techniques:

    • Base Editing: This technique allows scientists to change a single ‘letter’ in the DNA code without creating DSBs.
    • Prime Editing: This advanced technique builds upon CRISPR-Cas9, allowing for a wider range of precise DNA changes. It can correct most disease-causing mutations with enhanced safety and accuracy.
    • CASTs (CRISPR-associated transposases): This method enables larger DNA modifications without creating DSBs, offering a safer approach to genetic correction.

    Why does this matter for AMD and GA? These advancements in gene editing are crucial for addressing the genetic roots of these pathologies. We can potentially develop more effective and targeted therapies by precisely correcting the faulty genes that contribute to these diseases. The technologies are still being researched, but they hold great promise for the future of ophthalmology.

    Cell Reprogramming

    Cell reprogramming offers a novel approach to regenerative medicine, with the potential to replace damaged retinal cells. This technique involves changing a cell’s fate, either in vitro or in vivo. In vitro reprogramming involves extracting cells, reprogramming them in a laboratory, and then transplanting them back into the patient. In vivo reprogramming, which directly reprograms cells within the body, holds particular promise for retinal diseases. This approach has succeeded in preclinical studies, demonstrating the potential to restore vision in conditions like congenital blindness.

    future of ophthalmology

    Vectors and Delivery Methods

    The success of gene therapy relies on efficiently delivering therapeutic genes to target retinal cells. Vectors are essentially delivery vehicles, designed to carry therapeutic genes into cells. These vectors can be broadly classified into two categories: viral and non-viral. Vectors, both viral and non-viral, are crucial for this process.

    Viral vectors are modified viruses that have been engineered to remove their harmful components and replace them with therapeutic genes. They are highly efficient at delivering genes into cells, as they have evolved to do just that. Adeno-associated viruses (AAVs) are the most commonly used viral vectors in ocular gene therapy due to their safety profile and cell-specificity. The diversity of AAV serotypes allows for tailored gene delivery to specific retinal cell types.

    Non-viral vectors, on the other hand, are synthetic systems that don’t rely on viruses. They can be made from lipids, polymers, or even DNA itself. While they may be less efficient than viral vectors, they offer safety and ease of production advantages.

    Advances in vector design, whether viral or non-viral, are focused on enhancing gene expression, cell-specificity, and carrying capacity.

    Now, let’s examine the ongoing evolution of anti-VEGF treatments, a cornerstone of modern retinal care.

    New Anti-VEGF drugs

    The landscape of ophthalmology has undergone a dramatic transformation since the early 1970s when Judah Folkman first proposed the concept of tumor angiogenesis. His idea sparked research that ultimately led to the identification of vascular endothelial growth factor (VEGF) in 1989 and the development of anti-VEGF therapies, revolutionizing the treatment of neovascular eye diseases, dramatically improving outcomes for patients with wet AMD, diabetic retinopathy, and retinal vein occlusions.

    Population-based studies have shown a substantial reduction (up to 47%) in blindness due to wet AMD since the introduction of anti-VEGF therapies. However, significant gaps remain despite this progress, especially regarding treatment durability. Anti-VEGF drugs require frequent intravitreal injections, which can be difficult for patients due to time commitments, financial costs, and potential discomfort. Although newer agents have extended treatment intervals, patient adherence and undertreatment challenges persist in real-world settings. Innovative approaches are being investigated to address these unmet needs to increase drug durability and reduce the treatment burden.

    Tyrosine Kinase Inhibitors

    One approach to increasing treatment durability is using tyrosine kinase inhibitors (TKIs). TKIs are small-molecule drugs that act as pan-VEGF blockers by binding directly to VEGF receptor sites inside cells, offering a different action mechanism than traditional anti-VEGF drugs that target circulating VEGF proteins.

    Currently, TKIs are being investigated as maintenance therapy, primarily in conjunction with sustained-release delivery systems. Two promising TKIs for retinal diseases are axitinib and vorolanib. In a bioresorbable hydrogel implant, Axitinib is being studied for neovascular AMD and diabetic retinopathy. Vorolanib, in a sustained-release delivery system, is also being investigated for neovascular AMD. These TKIs offer the potential for less frequent dosing, reducing the treatment burden for patients.

    Port Delivery System

    The Port Delivery System (PDS) is a surgically implanted, refillable device that provides continuous ranibizumab delivery for up to 6 months. While it’s FDA-approved for neovascular AMD, it’s also being investigated for other retinal diseases, such as diabetic macular edema and diabetic retinopathy.

    future of ophthalmologySource

    Although the PDS faced a voluntary recall due to issues with septum dislodgment, it has returned to the market with modifications. The PDS offers the potential for significantly reduced treatment frequency for a subset of patients. However, challenges remain, including the need for meticulous surgical implantation and the risk of endophthalmitis.

    Nanotechnology

    Nanotechnology offers promising solutions to overcome limitations of current ocular drug delivery. The unique structure of the eye, with its various barriers, poses challenges for drug delivery. Topical administration often fails to achieve therapeutic concentrations, while frequent intravitreal injections carry risks. Nanotechnology can improve drug solubility, permeation, and bioavailability through nanoparticles, potentially extending drug residence time and reducing the need for frequent injections. Several nanoparticle systems, lipid and polymeric, are being studied for ocular drug delivery, offering hope for more effective and less invasive treatments.

    FDA-cleared AI for OCT analysis

    Demo Account Get brochure

    Summing up

    The advancements discussed in this article, encompassing AI, optogenetics, novel AMD/GA therapies, and refined anti-VEGF treatments, collectively signal a transformative era for ophthalmology. As highlighted by the survey results, AI probably encompasses most of the changes by redefining diagnostic and clinical workflows through its capacity for image analysis, biomarker identification, and personalized patient management.

    Optogenetics offers a distinct pathway to vision restoration, bypassing limitations of traditional gene therapy. The progress in AMD/GA treatments, particularly gene editing and cell reprogramming, presents opportunities for targeted interventions. Finally, the evolution of anti-VEGF therapies, with innovations in drug delivery and sustained-release mechanisms, addresses persistent challenges in managing neovascular diseases.

    These developments, driven by technological innovation and clinical research, promise to enhance patient outcomes and reshape the future of ophthalmic care.

popular Posted

  • Best AI for OCT: 10 Essential Features Your Platform Must Have 

    best AI for OCT
    Maria Martynova
    8 min.

    Best AI for OCT: 10 Essential Features Your Platform Must Have 

    So you’ve decided to trial AI for OCT analysis and wondering how to choose among all the available platforms. To save you some time, we’ve collected 10 most essential criteria according to which you can assess all existing AI platforms. Using this criteria you will be able to make an informed and rational choice.

    As an ophthalmologist, I am interested in finding innovative and modern approaches that could help me to enhance the workflow and improve patient outcome as a result.Analyzing various platforms, I realized that these 10 criteria are crucial for the right choice.

    1. Regulatory Compliance and Clinical Validation

    In healthcare, safety is always first. Regulatory approval and clinical validation are essential for AI-powered platforms for OCT scan analysis.

    The best AI OCT platforms should meet regulatory standards set by authorities such as the FDA, HIPAA, CE, and ISO. 

    Adhering to regulatory guidelines enhances credibility and fosters trust among healthcare professionals. Check if the AI for OCT analysis tool has all these certificates in place and if they are valid.

    FDA-cleared AI for OCT analysis

    Trial AI for OCT or learn more about it

    Demo Account Get brochure

     

    2.Wide range of biomarkers and pathologies detected

    Some AI for OCT platforms concentrate on certain pathologies, like  Age-Related Macular Degeneration (AMD) or Diabetic Retinopathy, because of the prevalence of these conditions among the population. It mostly means that eye care specialists must know in advance that they are dealing with the AMD patient to find the proof of AMD on the OCT.

    The best AI for OCT tools should have a wide variety of biomarkers and pathologies, including rare ones that cannot be seen daily in clinical practice, such as central retinal vein and artery occlusions, vitelliform dystrophy, macular telangiectasia and others. Altris AI, the leader of OCT for AI analysis, detects 74 biomarkers and pathologies as of today. 

    best AI for OCT

    3.Cloud-Based Data Management and Accessibility

    To ensure seamless integration into clinical workflows, the AI OCT platform should offer cloud-based data management and accessibility. Cloud storage allows for easy retrieval of patient records, remote consultations, and multi-location access. Secure cloud computing also enhances collaboration between ophthalmologists, optometrists, and researchers by enabling data sharing while maintaining compliance with data privacy regulations such as HIPAA and GDPR. 

    Many clinics have strict policies regarding patient data storage as well: it is crucial that the data is stored on the servers in the region of operation. If the clinic is in EU, the data should be stored in the EU.

    4.Real-world usage by eye care specialists

    When choosing the best AI for OCT analysis, real-world usage by eye care specialists is the most critical factor. Advanced algorithms and high accuracy metrics mean little if the AI is not seamlessly integrated into clinical workflows and actively used by optometrists and ophthalmologists. There are thousands of research models available, but when it comes to the implementation, most of them are not available to ECPs.

    Eye care professionals are not IT specialists. They require AI that is intuitive, fast, and reliable. If a system disrupts their workflow, generates excessive false alerts, or lacks clear explanations for its findings, adoption rates will be low—even if the technology itself is powerful. The best AI solutions are those that specialists trust and rely on daily to enhance diagnostic accuracy, streamline patient management, and support decision-making.

    Moreover, real usage generates valuable feedback that continuously improves the AI. Systems actively used in clinical settings undergo rapid validation, refinement, and adaptation to diverse patient populations. This real-world data is far more meaningful than isolated test results in controlled environments.

    5. Customizable Reporting and Visualization Tools

    Reports are the result of the whole AI for OCT scan analysis that is why customizable and comprehensive reports are a must.

    A high-quality AI OCT platform must offer customizable reporting and visualization tools. Clinicians should be able to adjust parameters, select specific data points, and generate detailed reports tailored to individual patient needs.

    Heatmaps, 3D reconstructions, and trend analysis graphs should be available to help visualize disease progression. These tools improve the interpretability of AI-generated insights and facilitate patient education.

    FDA-cleared AI for OCT analysis

    Trial AI for OCT or learn more about it

    Demo Account Get brochure

     

    6.AI for Early Glaucoma Detection

    Glaucoma is a leading cause of irreversible blindness, and since OCT is widely used to assess the retinal nerve fiber layer (RNFL), Ganglion Cell Complex ( GCC), optic nerve head (ONH), AI can significantly enhance early detection and risk assessment.

    Therefore, the best AI for OCT analysis tools have an AI for early glaucoma detection module available to assess the risk of glaucoma especially at the early stage. Moreover, tracking the progression of glaucoma with the help of AI should also be available for eye care specialists.  

    Clear and bright notifications about glaucoma risk are also vital for making AI glaucoma modules easy to use.  AI can provide proactive insights that enable early intervention and personalized treatment plans

    AI to detect glaucoma

    7.User – Friendly Interface and Intuitive Workflow Integration

    A well-designed AI OCT platform should feature a user-friendly interface that integrates seamlessly into existing clinical workflows. 

    It means that even non-tech-savvy eye care specialists should be able to navigate it effortlessly. 

    The interface should be intuitive, reducing the learning curve for healthcare providers. Features such as automated scan interpretation, voice command functionality, and guided step-by-step analysis can enhance usability and efficiency.

    8.Integration with Electronic Health Records (EHRs)

    For a seamless clinical experience, the AI OCT platform should integrate with existing electronic health record (EHR) systems. Automated data synchronization between AI analysis and patient records enhances workflow efficiency and reduces administrative burden. This feature enables real-time updates, streamlined documentation, and easy access to past diagnostic reports.

    9. Universal AI solutions compatible with all OCT devices

    Uf you want to use AI to analyze OCT, this AI should be trained on data received from various OCT devices and therefore should be applicable with various OCT devices. A vendor-neutral AI tool for OCT analysis provides unmatched advantages over proprietary solutions tied to specific hardware. By working seamlessly with multiple OCT devices, it eliminates the need for costly equipment upgrades and ensures broader accessibility across clinics and hospitals.

    This approach also fosters greater innovation, allowing AI models to continuously improve based on diverse datasets rather than being limited to a single manufacturer’s ecosystem. Vendor-neutral solutions integrate effortlessly into existing workflows, reducing training time and boosting efficiency. Clinicians benefit from unbiased, adaptable technology that prioritizes patient outcomes rather than locking users into restrictive ecosystems.

    10. Cost-Effectiveness and Accessibility

    To maximize its impact, an AI-powered OCT platform should be cost-effective and accessible to a wide range of healthcare providers. Affordable pricing models, including subscription-based or pay-per-use plans, can make AI technology available to smaller clinics and developing regions. Accessibility ensures that AI-driven OCT analysis benefits as many patients as possible, improving global eye health outcomes.

    FDA-cleared AI for OCT analysis

    Trial AI for OCT or learn more about it

    Demo Account Get brochure

    Conclusion

    What is the best  AI for OCT scan analysis? The best AI for OCT must be a comprehensive, intelligent, and adaptable platform that enhances diagnostic accuracy, streamlines clinical workflows, and supports proactive eye care. Key features such as high-accuracy automated analysis, multi-modal imaging integration, real-time decision support, cloud-based data management, interoperability, and explainable AI decision-making are crucial for an effective OCT AI system. By incorporating these attributes, AI-driven OCT platforms can revolutionize ophthalmology, enabling early disease detection, personalized treatment planning, and improved patient outcomes. As AI technology continues to advance, its integration with OCT will play an increasingly vital role in shaping the future of eye care.

     

  • Future of Ophthalmology: 2025 Top Trends

    future of ophthalmology
    Maria Znamenska
    13.03.2025
    12 min read

    Future of Ophthalmology: 2025 Top Trends

    In a recent survey conducted by our team, we asked eye care specialists to identify the most transformative trends in ophthalmology by 2025. The results highlighted several key areas, with artificial intelligence (AI) emerging as the clear frontrunner, cited by 78% of respondents.

    future of Ophthalmology

    However, the survey also underscored the significant impact of optogenetics, novel AMD/GA therapies, and the continuing evolution of anti-VEGF treatments. This article will explore the practical implications of these advancements, providing an overview of how they are poised to reshape diagnosis, treatment, research, and, ultimately, patient outcomes in ophthalmology.

    FDA-cleared AI for OCT analysis

    Demo Account Get brochure

     

    Building upon the survey’s findings, we begin with the most prevalent trend:

    AI in Ophthalmology

    future of opthalmology

    AI in Clinical Eye Care Practice

    With the increasing prevalence of conditions like diabetic retinopathy and age-related macular degeneration, there is a growing need for efficient and accurate screening tools. And AI is already valuable for eye-care screening: algorithms can analyze retinal images and OCT scans to identify signs of these diseases, enabling early detection and timely intervention.

    future of ophthalmology

    Source

    AI-powered screening tools can also help identify rare inherited retinal dystrophies, such as Vitelliform dystrophy and Macular telangiectasia type 2. These conditions can be challenging to diagnose, but AI algorithms can analyze retinal images to detect subtle signs that human observers may miss.

    future of ophthalmology

    Biomarkers of MacTel 2 detected and visualized by AI for OCT platform, Altris AI

    AI also starts to play a crucial role in glaucoma management. Early detection of glaucoma demands exceptional precision, as the early signs are often subtle and difficult to detect. Another significant challenge in glaucoma screening is the high rate of false positive referrals, which can lead to unnecessary appointments in secondary care and cause anxiety for patients—yet delayed or missed detection of glaucoma results in irreversible vision loss for millions of people worldwide. So, automated AI-powered glaucoma analysis can offer transformative potential to improve patient outcomes.

    One example of promising AI technology is Altris AI, artificial intelligence for OCT scan analysis, which has introduced its Advanced Optic Disc (OD) Analysis that provides a comprehensive picture of the optic disc’s structural damage, allowing detailed glaucoma assessment for treatment choice and monitoring.

    AI for Glaucoma Detection

    This OD module evaluates optic disc parameters using OCT, providing personalized assessments by accounting for individual disc sizes and angle of rim absence. Such a tailored approach eliminates reliance on normative databases, making evaluations more accurate and patient-specific.

    Furthermore, it enables cross-evaluation across different OCT systems, allowing practitioners to analyze macula and optic disc pathology, even when data originates from multiple OCT devices. Key parameters evaluated by Altris AI’s Optic Disc Analysis include disc area, cup area, cup volume, minimal and maximum cup depth, cup/disc area ratio, rim absence angle, and disc damage likelihood scale (DDLS).

    future of ophthalmology

     

    AI for Clinical Trials and Research

    AI is revolutionizing clinical trials and research in ophthalmology. One such key application of AI is biomarker discovery and analysis. Algorithms can analyze large datasets of medical images, such as OCT scans, to identify and quantify biomarkers for various eye diseases. These biomarkers can be used to assess disease progression, monitor treatment response, and predict clinical outcomes.

    AI is also being used to improve the efficiency and effectiveness of clinical trials. By automating the process of identifying eligible patients for clinical trials, AI can help researchers recruit participants more quickly and ensure that trials include appropriate patient populations, accelerating the development of new treatments.

    future of ophthalmology

    Algorithms can analyze real-world data (RWD) collected from electronic health records and other sources to generate real-world evidence (RWE). RWE provides valuable insights into disease progression, treatment patterns, and long-term outcomes in everyday clinical settings, complementing the findings of traditional randomized controlled trials.

    Oculomics

    Integrating digitized big data and computational power in multimodal imaging techniques has presented a unique opportunity to characterize macroscopic and microscopic ophthalmic features associated with health and disease, a field known as oculomics. To date, early detection of dementia and prognostic evaluation of cerebrovascular disease based on oculomics has been realized. Exploiting ophthalmic imaging in this way provides insights beyond traditional ocular observations.

    future of ophthalmology

    For example, the NeurEYE research program, led by the University of Edinburgh, is using AI to analyze millions of anonymized eye scans to identify biomarkers for Alzheimer’s disease and other neurodegenerative conditions. This research can potentially revolutionize early detection and intervention for these devastating diseases.

    Another effort spearheaded by researchers from Penn Medicine, Penn Engineering is exploring the use of AI to analyze retinal images for biomarkers indicative of cardiovascular risk. AI systems are being trained on fundus photography to detect crucial indicators, such as elevated HbA1c levels, a hallmark of high blood sugar, and a significant risk factor for both diabetes and cardiovascular diseases.

    future of ophthalmology

    Source

    AI analysis of retinal characteristics, such as retinal thinning, vascularity reduction, corneal nerve fiber damage, and eye movement, has shown promise in predicting Neurodegenerative diseases. Specifically, decreases in retinal vascular fractal dimension and vascular density have been identified as potential biomarkers for early cognitive impairment, while reductions in the retinal arteriole-to-venular ratio correlate with later stages.

    Moving from AI, we now turn to another significant trend identified in our survey:

    Optogenetics

    Optogenetics represents a significant leap forward in ophthalmic therapeutics, offering a potential solution for vision restoration in patients with advanced retinal degenerative diseases, where traditional gene therapy often falls short. While gene replacement therapies are constrained by the need for viable target cells and the complexity of multi-gene disorders like retinitis pigmentosa (RP), optogenetics offers a broader approach.

    future of ophthalmology

    This technique aims to circumvent the loss of photoreceptors by introducing light-sensitive proteins, known as opsins, into the surviving inner retinal cells and optic nerve, restoring visual function through light modulation. This method is particularly advantageous as it is agnostic to the specific genetic cause of retinal degeneration.

    By delivering opsin genes to retinal neurons, the technology enables the precise manipulation of cellular activity, essentially transforming these cells into new light-sensing units. This approach can bypass the damaged photoreceptor layer, transmitting visual signals directly to the brain.

    Several companies are pioneering advancements in this field. RhyGaze, for example, has secured substantial funding to accelerate the development of its lead clinical candidate, a novel gene therapy designed for optogenetic vision restoration. Their efforts encompass preclinical testing, including pharmacology and toxicology studies, an observational study to define clinical endpoints, and a first-in-human trial to assess safety and efficacy. The success of RhyGaze’s research could pave the way for widespread clinical applications, significantly impacting the treatment of blindness globally.

    future of ophthalmology

    Source

    Nanoscope Therapeutics is also making significant strides with its MCO-010 therapy. This investigational treatment, administered through a single intravitreal injection, delivers the Multi-Characteristic Opsin (MCO) gene, enabling remaining retinal cells to function as new light-sensing cells. Unlike earlier optogenetic therapies that required bulky external devices, MCO-010 eliminates the need for high-tech goggles, simplifying the treatment process and enhancing patient convenience. The ability to restore light sensitivity without external devices represents a major advancement, potentially broadening the applicability of optogenetics to a wider patient population.

    future of ophthalmology

    Source

    Another critical area of innovation highlighted in our survey is the advancement of treatments for AMD and GA.

    New AMD/GA Treatment

    Age-related macular degeneration (AMD) and geographic atrophy (GA) represent a significant challenge in ophthalmology, demanding innovative therapeutic strategies beyond the established anti-VEGF paradigm.

    future of ophthalmology

    Source

    Gene Correction

    Gene editing is emerging as a powerful tool in the fight against AMD and GA, potentially correcting the underlying genetic errors that contribute to these diseases. Essentially, it allows us to make precise changes to a patient’s DNA.

    Traditional gene editing techniques often rely on creating ‘double-strand breaks’ (DSBs) in the DNA at specific target sites, which are like precise cuts in the DNA strand. These cuts are made using specialized enzymes, like CRISPR-Cas9, which act as molecular scissors. While effective, these methods can sometimes introduce unwanted changes at the cut site, such as small insertions or deletions.

    After a DSB is made, the cell’s natural repair mechanisms kick in. There are two main pathways:

    • Non-Homologous End Joining (NHEJ): This is the cell’s quick-fix method. It essentially glues the broken ends back together. However, this process can sometimes introduce errors, leading to small insertions or deletions that can disrupt the gene’s function.
    • Homology-Directed Repair (HDR): This is a more precise repair method. It uses a ‘donor’ DNA template to guide the repair process, ensuring accuracy. However, HDR is more complex and less efficient, especially in non-dividing cells.

    To overcome these limitations of traditional gene editing, researchers have developed more precise techniques:

    • Base Editing: This technique allows scientists to change a single ‘letter’ in the DNA code without creating DSBs.
    • Prime Editing: This advanced technique builds upon CRISPR-Cas9, allowing for a wider range of precise DNA changes. It can correct most disease-causing mutations with enhanced safety and accuracy.
    • CASTs (CRISPR-associated transposases): This method enables larger DNA modifications without creating DSBs, offering a safer approach to genetic correction.

    Why does this matter for AMD and GA? These advancements in gene editing are crucial for addressing the genetic roots of these pathologies. We can potentially develop more effective and targeted therapies by precisely correcting the faulty genes that contribute to these diseases. The technologies are still being researched, but they hold great promise for the future of ophthalmology.

    Cell Reprogramming

    Cell reprogramming offers a novel approach to regenerative medicine, with the potential to replace damaged retinal cells. This technique involves changing a cell’s fate, either in vitro or in vivo. In vitro reprogramming involves extracting cells, reprogramming them in a laboratory, and then transplanting them back into the patient. In vivo reprogramming, which directly reprograms cells within the body, holds particular promise for retinal diseases. This approach has succeeded in preclinical studies, demonstrating the potential to restore vision in conditions like congenital blindness.

    future of ophthalmology

    Vectors and Delivery Methods

    The success of gene therapy relies on efficiently delivering therapeutic genes to target retinal cells. Vectors are essentially delivery vehicles, designed to carry therapeutic genes into cells. These vectors can be broadly classified into two categories: viral and non-viral. Vectors, both viral and non-viral, are crucial for this process.

    Viral vectors are modified viruses that have been engineered to remove their harmful components and replace them with therapeutic genes. They are highly efficient at delivering genes into cells, as they have evolved to do just that. Adeno-associated viruses (AAVs) are the most commonly used viral vectors in ocular gene therapy due to their safety profile and cell-specificity. The diversity of AAV serotypes allows for tailored gene delivery to specific retinal cell types.

    Non-viral vectors, on the other hand, are synthetic systems that don’t rely on viruses. They can be made from lipids, polymers, or even DNA itself. While they may be less efficient than viral vectors, they offer safety and ease of production advantages.

    Advances in vector design, whether viral or non-viral, are focused on enhancing gene expression, cell-specificity, and carrying capacity.

    Now, let’s examine the ongoing evolution of anti-VEGF treatments, a cornerstone of modern retinal care.

    New Anti-VEGF drugs

    The landscape of ophthalmology has undergone a dramatic transformation since the early 1970s when Judah Folkman first proposed the concept of tumor angiogenesis. His idea sparked research that ultimately led to the identification of vascular endothelial growth factor (VEGF) in 1989 and the development of anti-VEGF therapies, revolutionizing the treatment of neovascular eye diseases, dramatically improving outcomes for patients with wet AMD, diabetic retinopathy, and retinal vein occlusions.

    Population-based studies have shown a substantial reduction (up to 47%) in blindness due to wet AMD since the introduction of anti-VEGF therapies. However, significant gaps remain despite this progress, especially regarding treatment durability. Anti-VEGF drugs require frequent intravitreal injections, which can be difficult for patients due to time commitments, financial costs, and potential discomfort. Although newer agents have extended treatment intervals, patient adherence and undertreatment challenges persist in real-world settings. Innovative approaches are being investigated to address these unmet needs to increase drug durability and reduce the treatment burden.

    Tyrosine Kinase Inhibitors

    One approach to increasing treatment durability is using tyrosine kinase inhibitors (TKIs). TKIs are small-molecule drugs that act as pan-VEGF blockers by binding directly to VEGF receptor sites inside cells, offering a different action mechanism than traditional anti-VEGF drugs that target circulating VEGF proteins.

    Currently, TKIs are being investigated as maintenance therapy, primarily in conjunction with sustained-release delivery systems. Two promising TKIs for retinal diseases are axitinib and vorolanib. In a bioresorbable hydrogel implant, Axitinib is being studied for neovascular AMD and diabetic retinopathy. Vorolanib, in a sustained-release delivery system, is also being investigated for neovascular AMD. These TKIs offer the potential for less frequent dosing, reducing the treatment burden for patients.

    Port Delivery System

    The Port Delivery System (PDS) is a surgically implanted, refillable device that provides continuous ranibizumab delivery for up to 6 months. While it’s FDA-approved for neovascular AMD, it’s also being investigated for other retinal diseases, such as diabetic macular edema and diabetic retinopathy.

    future of ophthalmologySource

    Although the PDS faced a voluntary recall due to issues with septum dislodgment, it has returned to the market with modifications. The PDS offers the potential for significantly reduced treatment frequency for a subset of patients. However, challenges remain, including the need for meticulous surgical implantation and the risk of endophthalmitis.

    Nanotechnology

    Nanotechnology offers promising solutions to overcome limitations of current ocular drug delivery. The unique structure of the eye, with its various barriers, poses challenges for drug delivery. Topical administration often fails to achieve therapeutic concentrations, while frequent intravitreal injections carry risks. Nanotechnology can improve drug solubility, permeation, and bioavailability through nanoparticles, potentially extending drug residence time and reducing the need for frequent injections. Several nanoparticle systems, lipid and polymeric, are being studied for ocular drug delivery, offering hope for more effective and less invasive treatments.

    FDA-cleared AI for OCT analysis

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    Summing up

    The advancements discussed in this article, encompassing AI, optogenetics, novel AMD/GA therapies, and refined anti-VEGF treatments, collectively signal a transformative era for ophthalmology. As highlighted by the survey results, AI probably encompasses most of the changes by redefining diagnostic and clinical workflows through its capacity for image analysis, biomarker identification, and personalized patient management.

    Optogenetics offers a distinct pathway to vision restoration, bypassing limitations of traditional gene therapy. The progress in AMD/GA treatments, particularly gene editing and cell reprogramming, presents opportunities for targeted interventions. Finally, the evolution of anti-VEGF therapies, with innovations in drug delivery and sustained-release mechanisms, addresses persistent challenges in managing neovascular diseases.

    These developments, driven by technological innovation and clinical research, promise to enhance patient outcomes and reshape the future of ophthalmic care.

  • Altris AI Launches Advanced Optic Disc Analysis for Glaucoma, Complementing GCC Asymmetry Analysis

    Optic disc analysis
    Maria Znamenska
    1 min.

    Altris AI, a leading force in AI for OCT scan analysis that detects the widest range of retina pathologies and biomarkers, launches an advanced glaucoma Optic Disc Analysis module.  

    Early detection of glaucoma demands exceptional precision, as the early signs are often subtle and difficult to detect. A major challenge in glaucoma screening is the high rate of false positive referrals, which can lead to unnecessary appointments in secondary care. This not only burdens healthcare systems but also causes anxiety for patients. Yet delayed or missed detection of glaucoma results in irreversible vision loss for millions of people worldwide. So the need for timely and accurate glaucoma detection has never been so critical in the eye care industry, and automated AI-powered glaucoma analysis will offer a transformative potential to improve outcomes. 

    To address this critical need, Altris AI has introduced its Advanced Optic Disc (OD) Analysis, building on its earlier innovation with Ganglion Cell Complex (GCC) Asymmetry Analysis to enhance the improvements from the Altris AI macula module which has been available for several years.

    Optic disc analysis for glaucoma

    Altris AI’s glaucoma detection journey began with the creation of AI-powered GCC Asymmetry Analysis, designed to detect early risk of glaucoma.

    In February 2025 Altris launched the AI-powered Advanced Optic Disc (OD) Analysis module as OD analysis is regarded as the gold standard for structural glaucoma diagnosis.

    This method provides a comprehensive picture of structural damage and allows detailed glaucoma assessment for treatment choice and monitoring. 

    Optic Disc analysis

    The module evaluates optic disc parameters using OCT, providing personalized assessments by accounting for individual disc sizes and angle of rim absence. This tailored approach eliminates reliance on normative databases, making evaluations more accurate and patient-specific.

    Altris AI’s platform assigns a severity score for optic disc damage on a scale from 1 to 10, offering valuable insights into glaucomatous changes. Furthermore, it enables cross-evaluation across different OCT systems, allowing practitioners to analyze both macula and optic disc pathology, even when data originates from multiple OCT devices.

    Optic Disc Analysis for Glaucoma: Key Parameters 

    • Disc area
    • Cup area
    • Cup volume
    • Minimal Cup depth
    • Maximum Cup depth
    • Cup/Disc area ratio
    • Rim Absence angle
    • Disc-Damage Likelihood Scale (DDLS)

    The Altris AI Glaucoma Module is compatible with various OCT scan protocols, including:

    • 3D OCT optic disc scans
    • 3D OCT horizontal wide scans
    • 3D OCT vertical-wide scans
    • OCT optic disc raster scans

    By combining  GCC Asymmetry and Advanced Optic Disc analysis for glaucoma empower enabling Eyecare practitioners (ECPs) to make faster evaluations and explore a wider range of treatment options. This streamlined approach empowers ECPswith timely, actionable data, ultimately improving patient outcomes and care.

    Dr. Maria Znamenska, MD, PhD, and a Chief Medical Officer at Altris AI, commented:

    “The launch of our Advanced Optic Disc Analysis module marks a pivotal step forward in glaucoma care. By combining the gold standard of optic disc evaluation with AI-powered precision, we’re equipping eye care professionals with the tools to make more accurate and timely diagnosis of this vision-threatening disorder. This innovation not only reduces false positive referrals but also enhances early detection and treatment planning—ensuring better outcomes for patients and optimizing healthcare resources. Together with GCC asymmetry analysis, our platform empowers clinicians to elevate the standard of glaucoma care, offering hope to millions at risk of vision loss.”

     

    About Altris AI

    Altris AI is an artificial intelligence platform for OCT analysis, capable of detecting the widest range of retinal pathologies and biomarkers on the market – more than 70. Leading the way in AI innovation, Altris AI provides transformative solutions that enhance the diagnosis, treatment, and monitoring of retinal diseases, enabling eye care professionals to deliver exceptional patient care.

  • ML Applied to 3D Optic Disc Analysis for Glaucoma Risk Assessment Across Different OCT Scan Protocols Without a Normative Database

    Angelina Hramatik
    14.02.2025
    20 min read

    Machine Learning Applied to 3D Optic Disc Analysis for Glaucoma Risk Assessment Across Different OCT Scan Protocols Without a Normative Database

    1. Introduction

    Glaucoma is one of the leading causes of irreversible blindness worldwide, affecting millions of people annually. The disease is often asymptomatic in its early stages, making timely diagnosis particularly challenging. Early detection of glaucomatous changes is crucial for preventing vision loss and improving long-term patient outcomes. 

    One well-established method for assessing glaucoma is the Disc Damage Likelihood Scale (DDLS), which evaluates structural changes in the optic nerve head (ONH) based on the extent of neuroretinal rim loss. This method categorizes glaucomatous damage severity by analyzing the relationship between the optic cup and neural rim, while also accounting for optic disc size without relying on a normative database. 1, 2, 3, 4. 

    While DDLS is recognized for its reliability and utility in clinical practice, it is not a standalone diagnostic tool. Rather, it is one of several methods used to identify signs of glaucoma, and its implementation is often limited to specific imaging modalities or scan protocols, such as 3D optic disc-only scans or fundus images. 

    In this article, we introduce an enhanced approach to DDLS analysis that overcomes these limitations. We want to present a solution, which is capable of performing DDLS analysis on any OCT scan protocol that captures the optic nerve, including 3D optic disc scans (which provide the most detailed view of the nerve), as well as OCT horizontal and vertical 3D wide scans. By leveraging advanced machine learning models, we achieve unprecedented flexibility and accuracy, ensuring reliable analysis across different scanning protocols and OCT systems. 

    Unlike traditional systems restricted to specific devices or data formats, our solution processes scans from multiple OCT systems. Moreover, it excels in challenging scenarios, providing clinicians with a robust and versatile tool for analyzing potential signs of glaucoma. 

    FDA-cleared AI for OCT analysis

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    A Brief Theoretical Overview 

    Optical coherence tomography (OCT) scans vary in the anatomical regions they capture. One specific type is the optic disc OCT scan (Figure 2), which provides high-resolution imaging of the optic disc and the surrounding optic nerve head (ONH) structures. This scan type is commonly used in glaucoma assessment, as it allows for the evaluation of the optic nerve’s structure, including the neuroretinal rim, optic cup, and surrounding peripapillary retinal nerve fiber layer (RNFL) — key areas affected in glaucomatous damage. 

    disc likelihood damage oct

    Figure 1. Photograph of the retina of the human eye, with overlay diagrams showing the positions and sizes of the macula, fovea, and optic disc (Reference). 

    disc likelihood damage oct

    Figure 2. 6 mm OCT b-scan of the optic nerve head (ONH) region. 

    In contrast, macular OCT scans (Figure 3) focus on the central retina, providing detailed visualization of structures such as the foveal center, retinal layers, and macular biomarkers (such as drusen, hypertransmission, fluids etc). Since the macula is anatomically distinct from the optic nerve head, standard macular scans do not capture the ONH comprehensively. 

    ai oct optic disc analysis

    Figure 3. 6 mm OCT b-scan of the macular region, showing the foveal pit and retinal layers. 

    A more comprehensive scanning approach is 12 mm wide scan OCT (Figure 4), which captures both the macular region and optic nerve head in a single scan. This broader field of view allows for the simultaneous assessment of central retinal structures and optic nerve-related changes, making it valuable for detecting and monitoring conditions that affect both regions, such as glaucoma and other neurodegenerative or vascular retinal diseases. 

    3d wide glaucoma report

    Figure 4. 12 mm wide scan OCT b-scan, which captures both the macular region and part of the optic nerve head.

    2. Results

    2.1. Experiment Setup 

    Brief Method Overview 

    To evaluate the effectiveness of DDLS analysis in assessing glaucoma severity, we designed an experiment comparing results obtained from processing 3D Optic Disc OCT scans and 3D Wide scan OCT scans with the corresponding reports generated by the OCT system. Our method follows four key steps:  

    1. Detecting optic nerve landmarks like Bruch’s Membrane Opening (BMO) points (Eye Keypoints Retrieval / OCT Keypoint Detector Model); 
    2. Segmenting the inner limiting membrane (ILM) (Retina Layers Segmentation Model); 
    3. Reconstructing the neuroretinal rim geometry; 
    4. Applying the Disc Damage Likelihood Scale (DDLS) for classification.  

    The dataset below was used to validate the algorithm. 

    Dataset Used for Validating the Entire Algorithm 

    For validation, we compared our algorithm’s DDLS measurements with the DDLS values generated by the built-in algorithms of the Optopol REVO NX 130 OCT system. This provided a baseline for assessing accuracy and consistency. 

    To validate our approach, we conducted an experiment comparing DDLS metrics derived from: 

    • 3D Optic Disc OCT scans, which are traditionally used for DDLS analysis. 
    • 3D Wide scans, which capture both the macular and optic nerve regions, providing a more comprehensive dataset for analysis. 

    The dataset includes imaging data from 37 patients examined using the Optopol REVO NX 130 OCT system, with each patient undergoing the following protocols on the same day: 

    • 3D Optic Disc OCT (6mm zone): 168 scans 
    • 3D Wide scan (horizontal protocol, 12mm): 128 scans 

    A report was obtained from the 3D Optic Disc OCT scans, containing all parameters calculated by the device. 

    Since no manual annotations are available for these data, our comparison is conducted directly against the device-generated results. 

    The distribution of data was as follows: 

    • Glaucomatous Optic Disc: 21 cases; 
    • Normal Optic Disc: 16 cases. 

    2.2. Final Validation Results: DDLS Accuracy and Error Metrics 

    To evaluate the performance of our DDLS analysis method, we compared its results with the corresponding DDLS values generated by the OCT device’s built-in algorithms. The device reports serve as a reference point for all calculations, meaning the accuracy, MAE/STD values presented below indicate the level of agreement between our method and the device’s measurements. 

    The parameters compared below are the key indicators for glaucoma stage assessment. 

    • The rim-to-disc ratio (RDR) represents the thinnest neuroretinal rim width relative to the vertical optic disc diameter. A lower RDR indicates a more advanced stage of rim thinning, as glaucoma leads to progressive narrowing of the neuroretinal rim due to the loss of ganglion cells axons. 
    • The rim absence angle (RAA) quantifies the extent of neuroretinal rim loss in degrees. It defines the angle where the rim is completely absent, exposing the optic cup. A wider RAA suggests a more severe stage of glaucoma, as it indicates greater rim loss across the disc circumference. 

    Both RDR and RAA provide complementary perspectives on structural optic nerve damage: 

    • RDR measures the smallest remaining rim thickness in proportion to the disc. 
    • RAA evaluates how much of the disc circumference has lost its rim. 

    By considering both parameters together, a more comprehensive assessment of glaucoma severity can be achieved. Based on RDR and RAA, a DDLS stage is assigned, allowing for standardized classification of glaucoma progression. 

    ai oct optic disc analysis

    Table 1. Validation Results of DDLS Analysis on 3D Optic Disc and 3D Wide Scan OCT Scans 

    The table presents validation results comparing 3D Optic Disc OCT scan and 3D Wide scan OCT in DDLS analysis, focusing on Mean Absolute Error (MAE) and Standard Deviation (STD) for key parameters, along with overall DDLS staging accuracy. These metrics are calculated for the rim-to-disc ratio and rim absence angle by comparing their respective values from 3D Optic Disc OCT scans and 3D Wide scans against those from the device reports, providing a precise assessment of deviations from the reference values. 

    Key Observations

    1. Our Goal: Consistency with Device Reports, Not Outperformance

    The experiment does not aim to surpass the device’s accuracy but rather to demonstrate that our method produces results in alignment with the device-generated DDLS reports. 

    The device report serves as a reference, helping to interpret the figures we present, but this does not mean the device’s output is always the absolute truth. 

    2. High DDLS Staging Accuracy for Both Scan Types

    3D Optic Disc OCT scan: 97.3% accuracy in determining DDLS glaucoma stage. 

    3D Wide scan OCT: 94.59% accuracy, demonstrating strong reliability despite a broader scan area and fewer scans capturing the nerve, leading to less available information. 

    Conclusion: 

    • Both types of scans allow the production of clinically reliable DDLS results, but as expected, 3D optic disc scans provide slightly better accuracy due to their higher resolution of the optic nerve head (ONH). 
    • The small accuracy gap and close values for key parameters between the two suggests that 3D wide scan OCT can still be a viable option for glaucoma assessment, despite offering less detailed information about the optic nerve compared to optic disc scans. 

    3. RD Ratio and Rim Absence Angle: High Precision Within Clinical Margins

    RD Ratio (rim-to-disc ratio): 

    • Step size between DDLS stages: 0.1. 
    • Mean Absolute Error (3D Optic Disc OCT scan): 0.008 (significantly smaller than step size). 
    • Mean Absolute Error (3D Wide scan OCT): 0.024 (still relatively small). 

    Conclusion: 

    • Both 3D Optic Disc OCT scan and 3D Wide scan analysis provide high precision in RD ratio calculations. 
    • The small error ensures that stage classification remains reliable, especially in optic disc scans. 

    Rim Absence Angle: 

    • Step size between DDLS stages: Minimum 45°. 
    • Mean Absolute Error (3D Optic Disc OCT scan): 2.2° (very small compared to step size). Mean Absolute Error (3D Wide scan OCT): 4.2° (still well below stage transition threshold). 

    Conclusion: 

    • The method’s margin of error is far smaller than the clinical threshold for stage differentiation, confirming high accuracy in rim loss assessment. 
    • 3D Optic Disc scans again show better precision, reinforcing that they remain the preferred scan type for DDLS.

    4. Our Advantage: Ability to Perform DDLS on Both Scan Types

    • Unlike traditional DDLS implementations, which work only with 3D Optic Disc scans, our method can perform DDLS analysis on both 3D Wide scan and 3D Optic Disc OCTs. 
    • However, 3D Optic Disc OCT remains the preferred method for maximum precision, as it provides a higher-resolution view of the optic nerve. 

    Key Conclusions 

    1. Our method is unique in its ability to process multiple scan types, while still maintaining high accuracy in both cases. 
    2. On 3D Optic Disc scans, we achieve maximum precision, while on 3D Wide scans, we still maintain clinically reliable accuracy. 
    3. Consistency: Across all glaucoma stages, our method produced stable results that closely matched ground truths provided by medical experts. 
    4. Universal Compatibility: The algorithm performed equally well with scans from other manufacturers, demonstrating its versatility and robustness. 

    2.3. Patient Case Studies: DDLS Analysis in Real-World Scenarios 

    Accurate assessment of glaucoma severity relies on precise measurements of optic nerve parameters, such as disc area, rim-to-disc ratio, and rim absence angle. In the following examples, we analyzed four patient cases, including both normal optic discs and glaucomatous eyes, using 3D Optic Disc OCT scan, 3D Wide scan OCT, and device-generated reports as a reference standard. 

    By consolidating individual patient cases into a single comparative table, we can examine the consistency of DDLS analysis across different scan types and highlight key variations that may arise due to differences in scan coverage, segmentation accuracy, and anatomical structure. The following table summarizes the key optic nerve parameters measured for each patient and scan type. 

    AI OCT Optic Disc Analysis

    Table 2. Comparative DDLS Evaluation Across Multiple Patient Cases 

    Key Findings & Interpretation 

    1. High Consistency Between Our Method and Device Reports

    • Across all cases, the DDLS stage remains identical (4 for normal eyes, 7 or 8 for glaucomatous cases) regardless of whether the input scan was 3D Optic Disc OCT or wide scan, and this result corresponds to the device-generated report. 
    • Key optic nerve parameters such as disc area, cup area, and rim area closely align with the device reference, demonstrating strong algorithm performance. 

    2. Minor Variations in Cup and Rim Measurements

    • Cup and rim area values show slight deviations between 3D Optic Disc OCT scans and 3D Wide scan scans, which is expected due to differences in scan coverage and segmentation sensitivity. 
    • For example, in Patient 3 (Glaucoma, Stage 8): 
    • Cup area was 1.86 mm² (3D Optic Disc OCT scan), 1.88 mm² (3D Wide scan), and 1.81 mm² (Device Report). 
    • Rim area was 0.55 mm² (3D Optic Disc OCT scan), 0.53 mm² (3D Wide scan), and 0.58 mm² (Device Report). 
    • These small variations do not affect final DDLS staging but highlight how scan type can introduce subtle segmentation differences.

    3. Rim Absence Angle Varies Slightly but Remains Within Expected Tolerances

    • The rim absence angle shows minor fluctuations across scan types, especially in glaucomatous cases. 
    • Example: In Patient 3 (Stage 8 Glaucoma), the device reported a rim absence angle of 162°, while our algorithm calculated 155° (3D Optic Disc OCT scan) and 151° (3D Wide scan). 
    • Since DDLS categories for severe glaucoma are defined in large increments (e.g., 45°+ thresholds), these small differences do not impact staging accuracy.

    4. 3D Wide scan OCT Provides Comparable Results to 3D Optic Disc OCT scan

    • Despite covering a larger field of view, wide scans produced DDLS staging results consistent with 3D Optic Disc OCT scans and device reports. 
    • In patients with coexisting macular pathologies, 3D Wide scan OCT may provide additional clinical insights while still maintaining high reliability for glaucoma staging. 

    Conclusion: Reliable DDLS Analysis Across Different Scan Types 

    This unified case study analysis confirms that our DDLS analysis algorithm produces highly consistent results across different scan protocols and patient conditions. 

    1. DDLS stage assignment is identical to device reports across all scan types, ensuring high agreement with clinically validated reference values. 
    2. Key optic nerve measurements (disc area, cup area, rim area) are closely aligned across 3D Optic Disc OCT scan, 3D Wide scan, and device reports, reinforcing algorithm accuracy. 
    3. Minor variations in rim absence angle and segmentation metrics do not affect final glaucoma staging, highlighting the algorithm’s robustness. 
    4. 3D Wide scan OCT offers a viable alternative for 3D Optic Disc OCT scans, particularly in cases where both macular and optic nerve regions need simultaneous evaluation. 

    5. Visual Comparison Shows Strong Similarity to Device Reports

    1. The disk and cup boundaries detected by our algorithm closely match those in the device-generated reports, maintaining consistent shapes and anatomical alignment across both 3D Optic Disc and 3D Wide scan OCT scans. 
    2. However, wide scan-based segmentations tend to be slightly rougher, as less structural information is available compared to dedicated optic disc scans. This trade-off is expected due to the broader field of view in wide scans. 

    These findings validate our algorithm’s flexibility, adaptability, and clinical reliability, demonstrating its potential for seamless integration into real-world ophthalmic workflows. 

    2.4. Why Our Approach Stands Out: Key Advantages Over Traditional DDLS Systems 

    While the previous patient case studies demonstrated the accuracy and consistency of our DDLS analysis across different optic disc conditions, another critical advantage of our method is its ability to work seamlessly across various scanning protocols. Unlike traditional device-restricted solutions, our approach supports DDLS assessment on both standard 3D Optic Disc OCT scans and 3D Wide scans with different orientations. 

    The following table illustrates the same patient’s optic nerve head analyzed using three different scanning protocols: 3D Optic Disc OCT scan, 3D Wide scan Horizontal, and 3D Wide scan Vertical. This comparison highlights the method’s adaptability to different scan formats, ensuring reliable DDLS analysis regardless of the scanning protocol used. This example is taken from a Topcon Maestro 2 OCT system, providing an additional reference for processing across different OCT systems. 

    AI OCT Optic Disc Analysis

    Table 3. Comparative DDLS Analysis Across Different Scanning Protocols: 3D Optic Disc OCT, 3D Wide scan Horizontal, and 3D Wide scan Vertical. 

    This capability significantly enhances clinical applicability, allowing our algorithm to process data from various scanning protocols and devices while maintaining high accuracy. The ability to analyze both 3D Optic Disc and 3D Wide scan OCT scans — across different orientations and machine types — ensures comprehensive glaucoma assessment even in cases where scan availability or quality may vary. 

    Key advantages over traditional DDLS analysis methods 

    1. Device Independence

    1. While most existing solutions are restricted to proprietary OCT data formats, our algorithm processes scans from any OCT system, ensuring broad compatibility across devices. 

    2. Consistent Accuracy Across Different Scan Types 

    1. Our algorithm closely matches device-generated DDLS reports, achieving 97.3% accuracy for 3D Optic Disc OCT scans and 94.59% for 3D Wide scan OCTs. 
    2. Patient cases confirm this consistency, with both normal and glaucomatous eyes correctly classified, even when analyzed with different scan types. 

    3. Robust Performance in Edge Cases 

    1. Unlike traditional device-based DDLS assessments, which may struggle with low-quality images or atypical anatomical features, our approach maintains high accuracy in challenging clinical scenarios. 
    2. Patient examples with small optic discs and advanced-stage glaucoma demonstrated that our algorithm successfully identified key DDLS indicators even when scan quality or nerve structure was less distinct. 

    4. Expanded Assessment Through 3D Wide scan OCT 

    1. The ability to perform DDLS analysis on Horizontal and Vertical 3D Wide scans allows for a more comprehensive evaluation by incorporating both macular and optic nerve data. 
    2. In patients with coexisting macular pathologies, wide scans enabled earlier detection of glaucomatous changes that would have been missed if only optic disc scans were used. 

    3. Detailed Approach Description

    To assess glaucoma stage on OCT scans using DDLS analysis, the following steps should be performed: 

    1. Optic Nerve Landmarks Detection – Localization of the optic nerve in the b-scan view of each scan by identifying key anatomical landmarks. 
    2. ILM DetectionSegmentation of the inner limiting membrane (ILM) in the b-scan view of each scan to establish a reference for neuroretinal rim measurement. 
    3. Neuroretinal Rim Reconstruction – Construction of the neuroretinal rim geometry based on detected nerve landmarks and ILM segmentation. 
    4. DDLS Analysis – Application of the Disc Damage Likelihood Scale (DDLS) to assess glaucoma severity based on neuroretinal rim measurements. This includes assigning a DDLS stage according to rim width and optic disc size, with a focus on detecting localized thinning and asymmetry. 

    3.1. Keypoint Annotation Process / Nerve Detection 

    The foundation of our approach lies in a high-quality, annotated dataset meticulously labeled by a team of four expert ophthalmologists. The annotation process focused on identifying key anatomical landmarks in both the macular region and the optic disc nerve zones, both of which are critical for detecting glaucomatous changes and performing Disc Damage Likelihood Scale (DDLS) analysis. 

    These keypoints serve as essential data for evaluating disease progression and training machine learning models. The dataset was carefully selected based on key clinical features, such as the presence or absence of nerve fibers, foveal pits, and other pathological markers, ensuring a comprehensive representation of various conditions and scan types. 

    The annotated dataset consists of approximately 370 unique OCT examinations with more than 56,000 b-scans, covering a range of physical scanning areas, pathology types, and optic nerve conditions to enhance the model’s robustness. The scans are categorized as follows: 

    • Optic Disc with no excavation: ~15 examinations; 
    • Glaucomatous Optic Disc: ~105 examinations; 
    • Normal Optic Disc: ~105 examinations; 
    • Wide scans (covering both the macular and optic nerve regions): ~60 examinations; 
    • Normal Retina Scans: ~40 examinations; 
    • Pathological Retina Scans: ~45 examinations. 

    This detailed annotation process ensures high precision and reliability, enabling the algorithm to generalize across diverse cases while maintaining clinical accuracy in real-world scenarios. 

    3.2. Eye Keypoints Retrieval / OCT Keypoint Detector 

    Our keypoint detection model represents a logical evolution of the model for exam center detection, designed to efficiently and accurately identify key anatomical landmarks in OCT scans. The architecture integrates elements from UNet 5 and CenterNet 6, incorporating YOLO-inspired 7 techniques for keypoint prediction. Additionally, the backbone has been adapted to a transformer-based model 8, enhancing feature extraction capabilities. 

    Training Process 

    The training process follows a multi-stage approach, ensuring robustness, accuracy, and efficiency: 

    1. Stage 1: Detects general keypoints, establishing a foundation for precise landmark localization. 
    2. Stage 2: Groups and refines the identification of specific keypoints, progressively improving the model’s understanding of anatomical structures. 

    This structured approach enhances the model’s reliability across different scan types while maintaining computational efficiency. 

    Key Features 

    Data Preprocessing 

    • The data is augmented using unsupervised techniques, leveraging libraries such as Albumentations 9 to introduce variations such as rotations, scaling, and noise addition. 
    • This ensures the model encounters a wider variety of real-world scenarios during training, improving its generalization capability. 

    Training Process 

    • The model is trained using supervised learning techniques, optimizing a loss function through backpropagation and gradient descent. 
    • This approach allows for continuous refinement and adaptation to complex variations in OCT scans. 

    Parameterization & Tuning 

    • The model includes millions of adjustable parameters (weights), which are fine-tuned to increase accuracy. 
    • Key hyperparameters such as learning rate, batch size, and network depth are carefully selected to maximize performance. 
    • Advanced optimization techniques, including grid search, random search, and Bayesian optimization, are used to find the best hyperparameter configuration. 

    3.3. Retina Layers Segmentation Model 

    The Retina Layers Segmentation Model is our production-stage model, actively used within the Altris AI platform. It was incorporated into this experiment without modifications, ensuring that the results reflect real-world performance as seen in our deployed system. 

    Our Retina Layers Segmentation Model enables precise segmentation of key retinal layers in OCT scans, crucial for detecting structural changes linked to glaucoma and other retinal diseases. The model identifies: 

    • ILM, RNFL, GCL, IPL, INL, OPL, ONL, ELM, MZ, EZ, OS, RPE, BM 

    The training dataset consists of 5,000 expert-annotated OCT b-scans, covering a diverse range of patient demographics, including different ages and ethnic backgrounds. The segmentation model is designed to detect and delineate key retinal layers with high accuracy. 

    Training & Architecture 

    The model is based on U-Net with a ResNet backbone, optimized for OCT images. Training includes: 

    • Expert Annotation: Medical specialists labeled layers for ground truth. 
    • Augmentation: Albumentations-based transformations enhance robustness. 
    • Supervised Learning: Predicts segmentation masks using backpropagation. 
    • Hyperparameter Optimization: Grid search, random search, and Bayesian tuning maximize performance. 

    Model Validation & Performance 

    • The model was validated using a holdout validation approach, with separate validation and test sets that were not exposed during training. 
    • Real-world testing was conducted using scans from various clinical settings to ensure robustness. 
    • Performance was evaluated using the Mean Dice Coefficient across all layers, achieving a score of 0.80, with layer-specific scores ranging from 0.63 to 0.92, confirming high segmentation accuracy. 
    • Cross-domain testing demonstrated consistent performance across different OCT systems, and stability was confirmed over scans collected across different time periods. 

    This efficient, accurate, and generalizable model strengthens DDLS analysis and enhances AI-driven retinal diagnostics. 

    3.4. DDLS Algorithm 

    The DDLS algorithm evaluates glaucomatous changes by analyzing the geometric relationship between the neural rim and optic cup in the optic nerve head. Key steps include: 

    1. Localization: Identifying boundaries of the optic cup and neuroretinal rim by reconstructing geometry on a b-scan view using disc landmarks and an inner limiting membrane.

    3d wide glaucoma report

    Figure 5. B-scan Geometry Visualization. 

    1. Measurement: Calculating the DDLS stage based on the ratio between the rim and disc boundaries.
    2. Cross-Scan Application: Adapting the analysis for 3D Wide scans (both Horizontal and Vertical protocols) as well as 3D Optic Disc-specific scans.

    Our implementation enhances this traditional method by leveraging wide scans, enabling a more comprehensive assessment of glaucomatous changes. 

    3.5. Evaluation 

    To ensure the reliability and effectiveness of our DDLS algorithm, we conducted a rigorous evaluation process, adhering to best practices in data usage, ethics, and performance validation. 

    Data Integrity 

    • Measures were implemented to prevent data leakage, ensuring that scans from the same patient did not appear in both training and testing sets. 

    Ethical Considerations 

    • The analysis strictly relies on OCT-related data (e.g., scan zone size, laterality, pixel spacing) without incorporating any personal patient information. 

    Performance Metrics 

    • Keypoint detection accuracy was evaluated using Mean Squared Error (MSE), comparing model-predicted keypoints with expert annotations. 
    • Additional metrics included correctness of scan center-related landmarks and accuracy in the optic nerve region, ensuring precision in clinical applications. 

    The evaluation results confirmed the algorithm’s robustness, demonstrating significant performance gains, particularly in edge cases, where traditional methods often struggle. 

    Discussion 

    Our DDLS analysis method represents a significant advancement in glaucoma detection. Key benefits include: 

    1. Universal Compatibility: The ability to process data from various devices ensures broad applicability. 
    2. Enhanced Accuracy: By incorporating data from both macular and optic nerve regions, our approach captures more subtle glaucomatous changes. 
    3. Edge Case Performance: Advanced machine learning techniques enable accurate analysis even in challenging scenarios. 

    Compared to traditional methods, our system provides a more flexible, reliable, and comprehensive solution for early glaucoma detection. 

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    Conclusion 

    By integrating 3D Wide scans and state-of-the-art machine learning models, we have enhanced DDLS analysis for glaucoma detection, ensuring high accuracy, broad compatibility, and robustness across diverse clinical scenarios. 

    Unlike traditional solutions, our algorithm: 

    1. Works across multiple OCT devices, eliminating the constraints of proprietary data formats. 
    2. It closely matches device-generated DDLS reports, achieving 97.3% accuracy for 3D Optic Disc OCT scans and 94.59% for 3D Wide scans. 
    3. Performs reliably in edge cases, such as small optic discs and advanced-stage glaucoma, where traditional methods may struggle. 
    4. Supports both Horizontal and Vertical 3D Wide scans, enabling more comprehensive assessments that incorporate both macular and optic nerve data. 
    5. Enhances early glaucoma detection, particularly in patients with coexisting macular pathologies, where wide scans provide additional clinical insights. 

    By delivering consistently accurate DDLS staging, regardless of scan type or manufacturer, our system establishes a new benchmark for universal glaucoma assessment. This technology has the potential to significantly improve early detection and management, ultimately preserving vision and enhancing patient outcomes. 

    References 

    1. Spaeth, G. L. (2005). The Disc Damage Likelihood Scale. Glaucoma Today. https://glaucomatoday.com/articles/2005-jan-feb/0105_18.html 
    2. Cheng, K. K. W., & Tatham, A. J. (2021). Spotlight on the Disc-Damage Likelihood Scale (DDLS). Clinical Ophthalmology, 15, 4059–4071. https://pmc.ncbi.nlm.nih.gov/articles/PMC8504474/ 
    3. Zangalli, C., Gupta, S. R., & Spaeth, G. L. (2011). The disc as the basis of treatment for glaucoma. Saudi Journal of Ophthalmology, 25(4), 381-387. https://www.sciencedirect.com/science/article/pii/S1319453411000993 
    4. Review of Optometry Staff. (2023, January 23). Optic disc staging systems effective in grading advanced glaucoma. Review of Optometry. https://www.reviewofoptometry.com/article/optic-disc-staging-systems-effective-in-grading-advanced-glaucoma 
    5. Ronneberger O, Fischer P, Brox T. U-Net: Convolutional Networks for Biomedical Image Segmentation. [Preprint]. Posted May 18, 2015. https://arxiv.org/abs/1505.04597 
    6. Duan K, Bai S, Xie L, et al. CenterNet: Keypoint Triplets for Object Detection. [Preprint]. Posted April 17, 2019. https://arxiv.org/abs/1904.08189 
    7. Redmon J, Divvala S, Girshick R, Farhadi A. You Only Look Once: Unified, Real-Time Object Detection. [Preprint]. Posted June 8, 2015. https://arxiv.org/abs/1506.02640 
    8. Dosovitskiy A, Beyer L, Kolesnikov A, et al. An Image is Worth 16×16 Words: Transformers for Image Recognition at Scale. [Preprint]. Posted October 22, 2020. https://arxiv.org/abs/2010.11929 
    9. Buslaev A, Iglovikov V, Khvedchenya E, et al. Albumentations: Fast and Flexible Image Augmentations. [Preprint]. Posted September 18, 2018. https://arxiv.org/abs/1809.06839
  • Altris AI Introduces Next-Generation Fluids and GA Quantification Features

    Maria Znamenska, MD, PhD Ophthalmology
    1 min. read

    Altris AI Introduces Next-Generation Fluids and GA Quantification Features

    Altris AI, a pioneering force in artificial intelligence for OCT scan analysis, has unveiled additional quantification features for Fluids and Geographic Atrophy (GA) tracking on its web platform. Altris AI currently detects over 70 retina pathologies and biomarkers. However, we have decided to enhance its capabilities by adding additional Fluids and GA quantification and tracking functionalities, recognizing that eye care specialists frequently work with these conditions.

    These advancements empower eye care professionals (ECPs) with cutting-edge tools for diagnosing and managing retinal diseases. By integrating AI-driven quantitative tracking and progression monitoring, Altris AI enables specialists to deliver more personalized and effective treatments, ultimately enhancing patient outcomes.

    Fluids Quantification and Progression Tracking

    The presence of fluids such as Intraretinal Cystoid Fluid (IRC), Diffuse Edema, Subretinal Fluid (SRF), and Serous Retinal Pigment Epithelium (RPE) Detachment are critical biomarkers for conditions like nAMD, DME, DR, and RVO. Accurate detection, quantification, and tracking of these fluids are essential for monitoring disease activity, evaluating treatment efficacy, and making informed prognoses.

    We created specialized more detailed functions which detect these biomarkers for more specific and accurate tracking. The AI algorithm was additionally trained to work directly with fluids taking into account the importance of these biomarkers for accurate diagnostics.

    Altris AI’s advanced algorithms, trained on millions of OCT scans, provide precise and objective fluid analysis. Each of the four fluid types is localized and color-coded for clarity. Quantitative metrics such as volume, area, and ETDRS grids (1, 3, and 6 mm) are calculated and presented in mm3 or nanoliters for comprehensive evaluation. The Progression Tracking feature offers historical trend analysis with intuitive visualizations through graphs and percentages. For instance, if Cystoid Fluid (IRC) increases in volume, ECPs can immediately identify and address the change.

    Precision in Geographic Atrophy (GA) Monitoring

    Recent advancements in GA treatment have led to a growing need for large-scale screening in clinical practice. However, this increased demand often means higher workloads and less time for in-depth analysis. 

    The platform facilitates automated detection, quantification, and tracking of GA by analyzing key biomarkers: Pigment Epithelium (RPE) atrophy, Hypertransmission, Neurosensory Retina Atrophy, and Ellipsoid Zone (EZ) disruption. These biomarkers are color-coded for easier identification. 

    We assess GA using three key criteria:

    1. Overlapping region of 3 biomarkers: Hypertransmission, RPE Atrophy, and Neurosensory Retina Atrophy (referred as the GA zone).
    2. The shortest distance from the Fovea center to the GA zone.
    3. Percentage of the GA zone covering the 1 mm, 3 mm, and 6 mm ETDRS grid areas.

    AI for GA

    We also improved the accuracy of a critical step in our AI pipeline: the fovea and central scan detection. Altris AI’s updated model is much more robust in detecting fovea zone and central scan now. Especially in cases when the center cannot be distinguished due to pathology presence or other reasons, the model is trained to analyze the whole surface and find reference locations from which a central scan could be determined. The new model can find an accurate center in 95% of cases, in other situations, it can efficiently estimate the center location (as opposed to a simple analysis flow used by ECPs where the geometrical center is selected). This advancement significantly enhances the precision of GA detection.

    Further Progression Tracking enhances GA management by visualizing changes over time, supporting timely and accurate treatment decisions. By streamlining workflows and providing actionable insights, this feature helps ECPs make informed choices and potentially preserve vision in GA patients.

    Dr. Maria Znamenska, MD, PhD, and a Chief Medical Officer at Altris AI, commented:

    “We listened to our clients and introduced Fluids and GA tracking features. In 2025, eye care specialists will have the tools to combine their expertise with next-generation AI technology to effectively tackle conditions that threaten vision. Our formula is simple: detect, quantify, and track fluids, GA, and 70+ retina pathologies and biomarkers for better patient outcomes.”

    About Altris AI

    Altris AI is an artificial intelligence platform for OCT analysis that detects the widest range of retina pathologies and biomarkers on the market – more than 70. Leading the way in AI innovation, Altris AI provides transformative solutions that enhance the diagnosis, treatment, and monitoring of retinal diseases, enabling eye care professionals to deliver exceptional patient care.

  • OCT Scan Normal Eye vs 8 Most Common Pathologies

    normal abnormal oct scan
    Maria Znamenska
    31.10.2024
    14 min read

    OCT Scan Normal Eye vs. 8 Most Common Pathologies

    Differentiating between an OCT scan of a normal eye vs. a pathological one is a practical skill gained after years and years of practice. However, educating yourself on the basic differences will speed up the process. Understanding the “why” and “how” behind any changes on the OCT scan, compared to a normal macula OCT, will speed up your learning curve and deepen your expertise as a retinal expert.

    The article’s first part focuses on key OCT features and their meaning as a structural change for retinal architecture. The second part discusses the most recognizable OCT features of eight common pathologies.

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    OCT Scan: Normal Eye

    When evaluating an OCT scan, the most logical step is to understand how a normal macula OCT should look. The most telling feature across all scans is the contrast between light and dark areas. Typically, the nerve fiber layer and the underlying ganglion cell layer appear brighter than the densely packed nuclear layers. This is followed by the inner plexiform layer interface, which presents as a bright, hyperreflective area.

    The inner nuclear layer, composed of densely packed nuclei, appears dark. This is followed by the outer plexiform layer, the outer nuclear layer, and Henle’s layer. The external limiting membrane, an important landmark for assessing retinal health, is also visible. The ellipsoid zone (EZ) is another bright layer, while the interdigitation zone may not always be distinguishable from the underlying RPE layer, even in healthy eyes. Finally, the RPE and inner choroid appear hyperreflective.

    normal macula oct

    Structure

    The ELM and EZ are critical structures to assess. In a normal macula OCT, the distance between the EZ and ELM is shorter than between the EZ and the RPE. The apparent “elevation” of the EZ in the foveal center results from the elongated outer segments of the foveal cones.

    It’s important to remember that not all retinal structures are readily visible on a normal macula OCT. For example, Henle’s fiber layer is more easily distinguished in the presence of retinal pathology, such as swelling or thinning. Similarly, Bruch’s membrane is usually not visualized unless there is a separation between the RPE and Bruch’s membrane, often indicative of disease.

    Thickness

    Choroidal thickness is another key factor in OCT assessment. A general rule of thumb is that the choroid (between the RPE and the outer choroidal boundary) is approximately as thick as the retina. Thinning of the choroid may be observed in myopic or older patients, while marked choroidal thickening can raise suspicion for diseases like central serous retinopathy.  

    The OCT scan also provides information about laterality. The nerve fiber layer is characteristically thicker near the optic nerve head.  Conversely, if the nerve fiber layer is not visualized in its expected location on an otherwise OCT normal scan, it could signal significant nerve fiber layer loss, potentially due to glaucoma or other optic neuropathies.

    Reflectivity

    Specific OCT terminology helps describe scans and differentiate normal findings from pathology.

    Two fundamental concepts in OCT interpretation are hyporeflectivity and hyperreflectivity, which form the basis for understanding the structural composition of the retina as visualized in an OCT scan.

    Hyporeflectivity refers to the increased light transmission capacity of a structure. The OCT scanning laser beam passes through hyporeflective structures with minimal reflection. The quintessential example of a hyporeflective structure is the vitreous humor. It appears as a dark area in the uppermost portion of a normal OCT scan, situated above the retina.

    But hyporeflectivity can also be pathological, deviating from the patterns observed in a normal macula OCT; in the retina, it manifests in three primary ways.

    Like the vitreous, subretinal fluid exhibits high light transmission and appears black on OCT. A uniformly black region suggests the fluid lacks cellular debris or other inclusions.

    normal abnormal oct scan

    Subretinal fluid on OCT

    Fluid can also accumulate within the retinal layers, for example, between the layers of the neuroepithelium. This intraretinal fluid also appears hyporeflective on OCT.

    oct scan normal eye

    Intraretinal fluid on OCT

    Following a degenerative process within the retina, a cavity or void may form where retinal tissue has been lost. These degenerative cavities lack the cellular components necessary to reflect light and thus appear as dark spaces on OCT.  It’s important to differentiate these cavities from cystic spaces, which may have distinct clinical implications.

    One example is outer retinal tubulations. While associated with various diseases, outer retinal tubulations (ORTs) generally indicate outer retinal degeneration and atrophy.

    normal macula oct

    Outer retinal tubulations on OCT

    Hyperreflectivity, unlike hyporeflectivity, indicates structures with high light reflectance. On the grayscale spectrum of an OCT image, hyperreflective structures appear progressively whiter. 

    The retinal pigment epithelium (RPE) complex and Bruch’s membrane are considered the most hyperreflective structures in a normal macula OCT.

    Pathological processes can introduce new hyperreflective elements within the retina, aiding in differentiating normal and abnormal OCT scans. A typical example is hard exudates, frequently observed in diabetic retinopathy. These lipid-rich deposits are extremely dense, causing them to appear bright white on OCT due to the complete reflection of incident light. Furthermore, this high density leads to a shadowing effect beneath the deposits, caused by strong backscattering of the OCT signal.

    normal abnormal oct scan

    Hard exudates and shadowing on OCT

    Epiretinal membranes (ERMs) – a thin membrane or layer of scar tissue that forms over the retina – are also hyperreflective. It is composed of dense connective tissue with high light-reflecting properties and appears white on OCT scans.

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    Integrity

    Beyond hypo- and hyperreflectivity, OCT interpretation involves assessing the structural integrity of retinal layers. For instance, in an OCT scan of a normal eye, Bruch’s membrane appears as a thin, continuous line underlying the retinal pigment epithelium (RPE). The RPE is a monolayer of cells, ideally presenting with a smooth and uniform optical density. However, some pathologies, particularly early stages of age-related macular degeneration (AMD), may show unevenness or integrity loss in the RPE and Bruch’s membrane complex. 

    Disruption of the ellipsoid zone (EZ) is a particularly concerning finding on OCT, often indicating photoreceptor damage. Significant disruption of the EZ in the central macula is a strong biomarker for adverse visual outcomes.

    The closer the loss of integrity extends toward the foveal center, the poorer the visual prognosis tends to be.

    oct scan normal eye

    Ellipsoid zone disruption on OCT

    OCT also plays a crucial role in visualizing and characterizing breaks in the structural integrity of the retina. These breaks, commonly referred to as retinal tears or holes, can be classified as full-thickness or partial-thickness, depending on the extent of retinal involvement.

    Full-thickness breaks completely separate all retinal layers, while partial-thickness breaks involve only some retinal layers. OCT allows for precise delineation of the layers involved and the overall morphology of the break.

    Retinal holes can also be categorized by their location. Macular holes, as the name suggests, involve the central retina and can lead to significant central vision loss and require prompt attention.

    normal macula oct

    Lamellar macular hole on OCT

    Non-macular holes occur outside the central macular region, often in the peripheral retina. While they may not cause immediate central vision disturbances, they can still lead to serious complications, such as retinal detachment, if left untreated.

    Definition

    The blurring of retinal structures, or loss of definition, is another key OCT concept. This loss of the retina’s normal layered organization, seen in diseases like AMD, manifests as indistinct layers merging into a homogenous mass.

    normal macula oct

    Disorganisation of retinal inner layers on OCT

    Hypertransmission in OCT refers to enhanced signal penetration due to reduced blockage of the OCT light signal. This phenomenon is frequently observed in geographic atrophy, a late stage of AMD characterized by the atrophy of the retinal pigment epithelium, choriocapillaris, and photoreceptors.

    normal abnormal oct scanHypertransmission on OCT

    In a normal macula OCT, a signal is attenuated as it traverses the various retinal layers, with a portion of the signal being reflected to the detector. However, in geographic atrophy (GA), the loss of RPE and other retinal structures reduces this attenuation, allowing the OCT signal to penetrate deeper into the choroid. This increased penetration results in a stronger signal return from the choroidal layers, creating essentially a “corridor” of enhanced signal penetration through the atrophic areas of the retina.  This deep penetration and strong signal return, unfortunately, indicate significant retinal damage and are associated with a poor visual prognosis.

    Displacement

    Another term used to describe OCT scan results is elevation. It refers to the upward displacement of retinal structures from their normal anatomical position. In the context of age-related macular degeneration (AMD), elevation is frequently associated with the presence of drusen.

    Drusen are extracellular deposits that accumulate between the retinal pigment epithelium (RPE) and Bruch’s membrane. They are a hallmark of AMD and can vary in size, shape, and composition.  Drusen are typically categorized as hard, soft, or confluent based on their ophthalmoscopic appearance.

    oct scan normal eye

    Hard and soft drusen on OCT

    In contrast to elevation, depression in OCT describes the inward displacement or concavity of retinal structures.  This can be a manifestation of various pathological processes, with a prominent example of degenerative myopia.

    oct scan normal eye

    Degenerative myopia on OCT

     

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    OCT scan: normal eye transformation through pathologies

    Age-related macular degeneration (AMD)

    AMD is an acquired degenerative macular disease usually affecting individuals over the age of 55 years. It is characterized by pathologic alterations of the outer retina, retinal pigment epithelium (RPE), Bruch’s membrane, and choriocapillaris complex, including drusen formation and pigmentary changes.

    AMD is a progressive disease, and in advanced stages, central geographic atrophy and neovascularization, may develop and reduce vision. OCT plays a critical role in distinguishing between the different stages and forms of AMD, particularly when compared to the features of an OCT normal scan.

    Wet AMD

    normal abnormal oct scan

    Neovascular or “wet” age-related macular degeneration (nAMD) arises from the aberrant growth of choroidal vessels that penetrate Bruch’s membrane and invade the subretinal space. These abnormal vessels leak fluid and blood, disrupting the retinal architecture and causing vision loss. 

    Several key OCT features can signal the presence and activity of nAMD in comparison to a normal OCT scan:

    • Fluid Accumulation: The presence and location of fluid are hallmarks of nAMD (hence the term ‘wet AMD’). Intraretinal fluid, appearing within the retinal layers, often signifies more severe disease and a poorer visual prognosis than subretinal fluid, which accumulates beneath the retina.
    • RPE Detachment: Serous PED appears as a dome-shaped elevation of the RPE due to fluid accumulation beneath it. PEDs often accompany nAMD and can vary in size and shape.
    • Disruption of Retinal Layers: nAMD can disrupt the normal retinal architecture, particularly the photoreceptor layer. Damage to the ellipsoid zone (EZ) and external limiting membrane (ELM) is visible on OCT and correlates with visual impairment.
    • Hyperreflective Foci: Hyperreflective dots (HRDs) are small, bright spots scattered throughout the retina.
    • Subretinal Hyperreflective Material (SHRM): Appears as a hyperreflective band between the retina and RPE. Its composition varies but may include fluid, fibrin, blood, and neovascular tissue; it can be associated with poorer visual outcomes.
    • RPE Tears: These are disruptions in the RPE monolayer, often occurring in areas of PED. RPE tears can lead to significant vision loss and are an important complication of nAMD.
    • Choroidal Changes: nAMD can also affect the choroid, the vascular layer beneath the RPE.

    Dry AMD

    normal abnormal oct scan

    In its early stages, Dry AMD is characterized by drusen and pigmentary abnormalities resulting from alterations in the retinal pigment epithelium (RPE). Later, it can progress to geographic atrophy (GA) or outer retinal atrophy.

    The three classic findings in Dry AMD are drusen, pigmentary changes, and geographic atrophy.

    Drusen are classified as:

    • small (<65 um), 
    • medium (65 – 124 um), 
    • or large (>125 um). 

    While both drusen and pigmentary changes can appear as yellowish deposits in the retina, pigmentary changes are often more varied in color (ranging from yellow to brown or black) and less defined in shape than the generally circular drusen.

    Geographic atrophy typically begins in the paracentral macula, often surrounding the fovea in a horseshoe pattern. It can eventually involve the fovea itself, leading to severe vision loss.

    Diabetic Retinopaty (DR)

    normal macula oct

    Diabetic retinopathy (DR), a leading cause of vision loss in working-age populations, is characterized by retinal vascular abnormalities. It progresses from non-proliferative DR (NPDR), marked by vascular leakage and capillary occlusion, to proliferative DR (PDR), where neovascularization can lead to severe vision impairment through vitreous hemorrhage or retinal detachment.

    OCT can aid in identifying the earliest sign of DR: microaneurysms. They appear as small, distinct, oval-shaped, hyperreflective, walled structures associated with microvascular damage. Specifically, the structural weakness of the vessel wall of MAs causes fluid leakage, resulting in edema.

    oct scan normal eye

    Another consequence of microaneurysm formation is the progression to intraretinal hemorrhages (IRH), often called ‘dot-blot’ hemorrhages. These appear as hyperreflective foci on OCT cross-sections, with varying degrees of opacification.

    Diabetic macular edema (DME) can occur at any stage of the disease and is the most common cause of vision loss in those with diabetes. It results from a blood-retinal barrier breakdown, leading to fluid leakage and retinal thickening.

    Retinal vein occlusions

    normal macula oct

    Retinal vein occlusions (RVOs) are blockages of the retinal veins responsible for draining blood from the retina. These blockages can affect either the central retinal vein (CRVO) or one of its branches (BRVO). RVOs are more prevalent in older individuals and those with underlying vascular conditions such as high blood pressure, high cholesterol, a history of heart attack or stroke, diabetes, or glaucoma. The primary vision-threatening complications of RVO are macular edema, which involves fluid accumulation in the central retina, and retinal ischemia, which results from insufficient blood flow to the retina.

    While both Central Retinal Vein Occlusion (CRVO) and Branch Retinal Vein Occlusion (BRVO) involve blockage of a retinal vein, the underlying cause and location of the blockage differ.

    CRVO occurs when a thrombus (blood clot) blocks the central retinal vein near the lamina cribrosa, where the optic nerve exits the eye.

    In contrast, BRVO typically occurs at an arteriovenous crossing point, where a retinal artery and vein intersect. Atherosclerosis (hardening of the arteries) can compress the vein at this crossing point, leading to thrombus formation and occlusion.

    In CRVO, the retina often exhibits extensive intraretinal hemorrhages, dilated and tortuous veins, and cotton-wool spots. This constellation of findings is classically described as a “blood and thunder” appearance. In BRVO, the signs are typically localized to the area of the retina drained by the affected vein. Macular edema, characterized by retinal thickening and cystoid spaces within the retina, is a common finding in CRVO and BRVO and can significantly contribute to vision loss.

    Central serous retinopathy

    normal abnormal oct scan

    Central serous chorioretinopathy (CSCR) is a common retinal disorder that causes visual impairment and altered visual function. It is classified as a pachychoroid disease, including conditions like polypoidal choroidal vasculopathy and pachychoroid neovasculopathy. 

    OCT imaging in CSCR often reveals a thicker-than-average choroid.

    This diagnostic is particularly useful in cases where clinical examination findings are inconclusive, distinguishing subtle differences between normal and abnormal OCT scans in terms of structural changes, such as small pigment epithelial detachments (PEDs) and hyperreflective subretinal fluid, that may not readily appear on clinical exams.

    Furthermore, OCT is valuable for monitoring disease progression and resolution in chronic CSCR cases. A distinguishing feature that can also be seen in CSR is the appearance of the retinal pigment epithelium: the RPE line typically appears straight in non-affected areas, while it can appear wavy or irregular in areas with CSCR.

    Epiretinal membrane (Epiretinal fibrosis) 

    oct scan normal eye

    Epiretinal fibrosis (epiretinal membrane/macular pucker) is a common condition affecting the central retina, specifically the macula. It is characterized by a semi-translucent, avascular membrane that forms on the retinal surface, overlying the internal limiting membrane (ILM), which is absent on a normal macula OCT.

    OCT plays a crucial role in assessing the severity of ERMs, revealing the extent of macular distortion and the involvement of retinal layers.

    OCT findings in ERMs are used to stage the severity of the membrane, ranging:

    • Stage 1: ERMs are mild and thin. Foveal depression is present.
    • Stage 2: ERMs with widening the outer nuclear layer and losing the foveal depression.
    • Stage 3: ERMs with continuous ectopic inner foveal layers crossing the entire foveal area.
    • Stage 4: ERMs are thick with continuous ectopic inner foveal and disrupted retinal layers.

    Retinal detachment

    normal abnormal OCT scan

    Retinal detachment is an important cause of decreased visual acuity and blindness, a common ocular emergency often requiring urgent treatment.

    It occurs when subretinal fluid accumulates between the neurosensory retina and the retinal pigment epithelium through three mechanisms:

    • Rhegmatogenous: a break in the retina allowing liquified vitreous to enter the subretinal space directly.
    • Tractional: proliferative membranes on the surface of the retina or vitreous pull on the neurosensory retina, causing a physical separation between the neurosensory retina and retinal pigment epithelium
    • Exudative: accumulation of subretinal fluid due to inflammatory mediators or exudation of fluid from a mass lesion/insufficient RPE function

    OCT helps identify foveal status and diagnose tractional or exudative retinal detachments, aiding in treatment planning.

    Macular hole

    normal macula oct

    Macular holes are full-thickness defects of retinal tissue involving the anatomic fovea and primarily the foveola of the eye. They are thought to form due to anterior-posterior forces, tangential forces and weakening in the retinal architecture that result in openings in the macular center. 

    The International Vitreomacular Traction Study (IVTS) Group formed a classification scheme of vitreomacular traction and macular holes based on OCT findings:

    • Vitreomacular adhesion (VMA): No distortion of the foveal contour; size of attachment area between hyaloid and retina defined as focal if </= 1500 microns and broad if >1500 microns
    • Vitreomacular traction (VMT): Distortion of foveal contour present or intraretinal structural changes in the absence of a full-thickness macular hole; size of attachment area between hyaloid and retina defined as focal if </= 1500 microns and broad if >1500 microns.
    • Full-thickness macular hole (FTMH): Full-thickness defect from the internal limiting membrane to the retinal pigment epithelium. Described 3 factors: 1) Size – horizontal diameter at narrowest point: small (≤ 250 μm), medium (250-400 μm), large (> 400 μm); 2) Cause –  primary or secondary; 3) Presence of absence of VMT.

    Glaucoma

    oct scan normal eye

    Glaucoma is a progressive optic neuropathy that is multifactorial and degenerative. It is characterized by the death of retinal ganglion cells (RGCs) and their axons, leading to the characteristic optic disc and retinal nerve fiber layer (RNFL) structural changes and associated vision loss. One of the most effective ways to get information about nerve states is OCT.

    The Glaucoma OCT test provides valuable information about ganglion cells: damage to the ganglion cells or their processes leads to thinning across respective layers, which we can measure as the thickness of the ganglion cell complex. 

    Key things to focus on when working with OCT for glaucoma detection:

    • Look for thinning of the pRNFL, particularly in the inferior and superior quadrants, asymmetrical thinning between a patient’s eyes
    • Assess the thickness of the ganglion cell-inner plexiform layer, macular RNFL, and the overall ganglion cell complex. 
    • Monitoring: Seek significant decreases over time in pRNFL thickness (≥5 μm globally, ≥7-8 μm in specific sectors) or in average GCIPL thickness (>4μm).

    AI-powered OCT interpretation tools, such as Altris AI, AI for OCT, can further assist clinicians by providing automated calculations of RNFL thinning in the upper and lower hemispheres and the asymmetry levels between them.

    FDA-cleared AI for OCT analysis

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    Summing up

    OCT has revolutionized ophthalmology, bringing a wealth of new details and challenges. The human eye can easily miss subtle abnormalities on complex scans, making accurate interpretation critical. While experience is essential, relying solely on  “learning by doing” poses risks. 

    AI-powered OCT interpretation software bridges this gap, offering a safety net during the learning curve and beyond. AI-powered second opinion on OCT scans enhances diagnostic accuracy, empowers clinicians, and allows them to spend more time for a meaningful connection with patients.

  • Optometry Practice Growth: Business Cases

    how to grow an optometry practice
    Altris Inc.
    03.10.2024
    8 min read

    Optometry practice growth: business cases

    The client. Dr. William C. Fruchtman’s Optometry Practice, owned and operated by Dr. William C. Fruchtman, O.D., is located in East Rutherford, New Jersey, an inner-ring suburb of New York City. With over 30 years of service to the community, the practice provides comprehensive eye care, including regular eye examinations, contact lenses, and glasses prescriptions. 

    Dr. William Fruchtman’s practice continually seeks opportunities to add value to its services. He is cultivating his expertise in dry eye disease and macular degeneration, implementing advanced technologies, and using another effective strategy to expand his patient base – communicating with patients in their preferred language. Knowing that clear communication is vital to good care, Dr. William C. Fruchtman’s team includes members who speak Spanish and Polish. As such, their website is available in both Polish and Spanish, a valuable asset considering the area’s substantial Spanish-speaking population (up to 20% of the local demographic).

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    While achieving fluency in every language spoken within your community may not be feasible, consider adapting your website and patient materials to include translations in commonly spoken languages. As Dr. Fruchtman’s experience confirms, even a simple greeting in a patient’s native language can create a bond with patients or, at the very least, prompt a genuine surprised smile.

    optometry practice growth

    The problem. To establish expertise in specialized services, Dr. William Fruchtman has been committed to effectively managing dry eye disease and macular degeneration. Not so long ago, the practice implemented Equinox Low-Level Light Therapy (LLLT). This advanced dry eye treatment utilizes LED lights to warm the eyelids gently, promoting meibomian gland function and oil release. With dry eye management addressed, Dr. Fruchtman sought an additional tool to both strengthen his decision-making when managing patients with other pathologies, particularly macular degeneration, and increase his optometry practice growth.

    The solution. After researching Altris AI, an Artificial Intelligence platform for OCT scan analysis, Dr. Fruchtman was positive that he wanted to try the platform. Following introductory meetings and a quick onboarding with the Altris team, he started a two-week trial. After personally testing the platform, Dr. Fruchtman decided it was an invaluable addition to his practice.

    optometry practice growth

    Integrating Altris AI into the practice has notably enhanced Dr. Fruchtman’s confidence and precision in diagnosing and managing eye care disorders. The practice has also gained a significant competitive advantage, as the platform can routinely perform Glaucoma Risk Analysis on existing OCT scans, offering additional value to patients. 

    Thanks to the color-coded and labeled OCTs, optometry facilitates patient education and enables practitioners and patients to monitor the progression or treatment results more effectively. 

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    How to grow an optometry practice: more cases from optometry owners

    Optometrists undergo years of education, training, practice, and continuous learning – understandably, it is hard to see additional time or resources to pursue business education. 

    Many practitioners experience stress, balancing patient care demands with the realities of running a profitable business. This feeling can intensify when attending countless conferences and webinars highlighting thousands of ways to make business more efficient. While they offer valuable advice, it’s sometimes helpful to remember simple points of how successful optometry practice growth will look: attracting new patients, retaining existing ones, and ensuring a smooth and efficient workflow. These (even though overly simplified) points allow you to focus on the most critical details.

    But before diving into ways of optometry practice growth, remember that the first step is a realistic assessment of your current situation. 

    While you’re likely aware of some issues, feedback from your team and patients can provide insights, and sometimes even immediate solutions, for areas of improvement. 

    Even though we cannot directly assist in assessing your specific practice, as you know it best, below we offer some key, proven strategies for growing your business.

    Optometry practice growth: expanding your patient base

    • Dry Eye Specialization

    One effective strategy for optometry practice growth is to expand the scope of services to include the diagnosis and management of ocular diseases. For example, dry eye disease (DED) affects ∼344 million people worldwide and over 20 million in the United States alone, yet many remain undiagnosed and untreated. This presents a significant opportunity to care for a large and often underserved patient population. By developing expertise in DED and offering specialized treatments, you can not only attract new patients but also contribute to improving the quality of life for those suffering from this chronic condition.

    how to grow an optometry practice

    There are numerous approaches to managing DED effectively. As mentioned, Dr. William C. Fruchtman’s practice utilizes Equinox Low-Level Light Therapy (LLLT). 

    Dr. Shane Swatts, O.D., owner of Eastern Virginia Eye Associates, employs AI software to enhance DED diagnostics, conduct more comprehensive analyses, and keep detailed patient medical histories. This technology upgrades pre-and post-operative care, saving time without compromising accuracy.

    how to grow an optometry practice

    • Aesthetic Optometry

    Dr. Janelle Davison identified an opportunity for optometry practice growth by addressing patient needs while generating additional revenue by incorporating aesthetic optometry services into her practice. Within a single quarter, her practice generated $14,000 in revenue from aesthetic product sales alone. 

    how to grow an optometry practice

    Source

    Dr. Davison also collaborates with a licensed aesthetician who operates within the practice on a contract basis, sharing the revenue generated from aesthetic services.

    improve efficiency in optometry office

    • Glaucoma Management

    Dr. James Deom, O.D., M.P.H., an optometrist from Pennsylvania, implemented a successful strategy for optometry practice growth based on attracting glaucoma patients, significantly increasing glaucoma-related revenue. He initiated internal marketing efforts by inquiring about patients’ family history of glaucoma and informing them about the practice’s newest technology for the early detection of vision loss.

    improve efficiency in optometry office

    Practices specializing in glaucoma management can significantly benefit from incorporating advanced software solutions to complement their existing diagnostic hardware. For instance, integrating Altris AI, AI for OCT,  into their OCT analysis workflow enables not only automated screening of 70+ pathologies and biomarkers but includes assessing retinal nerve fiber layer (RNFL) asymmetry for glaucoma risk evaluation.

    • Patient-Centered Care

    Offering diverse channels for patient interaction can broaden your practice’s reach and improve the patient experience. Dr. Melissa Richard, O.D., sought to provide patients with a preview of frame options before their appointments. To achieve this, she integrated Optify technology into her practice, a solution she discovered during a Vision Source Exchange lecture. This technology creates a virtual showroom where patients can explore and select their preferred frames in advance, streamlining the in-office experience.

    optometry practice growth

    Patient education is also key to patient-centered care and personalization, which not only empowers individuals and improves their outcomes but also fosters optometry practice growth. Those who understand their eye health are more likely to adhere to recommendations. 

    A study demonstrates that 94% desire educational content, but a third don’t receive it. 

    Providing color-coded OCT reports with pathologies, biomarkers, and pathology progression tracking not only satisfies this need but also elevates your practice above competitors.

    improve efficiency in optometry office

    Improve efficiency in the optometry office through strategic partnerships & team building

    When optometrists consider further career development, they may seek additional support to achieve their goals. Dr. Linda Enciso, O.D., found such support when her practice joined the AEG Vision family in 2019. The transition brought numerous positive changes, boosting patient care and fostering growth opportunities for team members.

    Although Dr. Enciso had already been operating her practice for 13 years and had implemented electronic health records (EHR) systems and third-party software to improve patient communication and boost optometry practice growth, her goal was to continue these advancements and expand the scope of practice.  Joining AEG Vision allowed her to transition to the training team, access continuing education opportunities to stay informed about advancements in optometry and healthcare, collaborate with other healthcare providers and cross-functional teams to enhance comprehensive patient care.

    optometry practice growth

    While the phrase “team building” might evoke images of complicated activities and extensive effort, fostering a strong team can be achieved through simple, engaging initiatives. Consider the inspiring example of Dr. Jonathan Cargo, O.D.  

    Dr. Cargo recognizes the value of personal development through reading but finds it challenging to share his insights with his team effectively. Inspired by his wife’s long-standing book club, he initiated an office book club to encourage team connection and shared learning to improve efficiency in the optometry office.

    The book club operates with team members suggesting relevant titles and collectively reading chapters over a month, dedicating time during team meetings for discussions. Dr. Cargo highlights the recent success of reading “Crucial Conversations,” a selection prompted by team members’ desire to deepen their communication skills, particularly in navigating challenging discussions with colleagues, patients, and even family members.  The shared reading experience gave a better understanding of effective communication strategies and empowered the team to navigate difficult conversations.

    improve efficiency in optometry office

     

    Summing up

    When regarding optometry practice growth, consider the time, effort, and resources you are prepared to invest. To expand your patient base, explore the addition of new services.

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    To optimize costs and efficiency and gain a competitive edge, investigate the possibility of implementing AI in your practice – it can be a second-opinion tool, or you can read here how practitioners use it for marketing, creating educational materials, and more. To encourage staff retention and nurture a positive work environment, prioritize team-building activities; even seemingly simple initiatives can produce significant benefits.

     

  • Optometry Trends in Action: 12 Real-World Success Stories

    Maria Znamenska
    17.09.2024
    8 min read

    Optometry Trends in Action: 12 Real-World Success Stories

    Optometry trends explained: showcasing real-world optometry practice owners who are adapting to the shift in patient needs, successfully implementing solutions to automate routine and laborious tasks, using AI to combat staff shortages, creating their own brand mascots, and more.

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    Optometry trends for the patient journey: digital communication

    Online shopping, global deliveries, and instant brand replies through messengers have dramatically shifted client expectations and behaviors. The ‘convenience economy’ isn’t slowing down, pushing businesses to adopt technology for more streamlined consumer experiences. 

    What does this mean for your practice? Your patients now expect fast and efficient communication across all touchpoints –  from online scheduling to contactless payments. Transforming your practice to meet these demands ensures satisfied patients and contributes to long-term success, as any optometry practice thrives on the individual experiences of the patients it provides.

    46% of optometrists reported that patient expectations have risen since the pandemic.

    Practices can optimize their workflows in various ways, but generally, the goal is to automate routine administrative tasks, free up staff, and reduce patient waiting time. Digital safety forms and document management systems eliminate physical paperwork, while online proofing and approval systems speed up document processing.

    Optometry trends

    Dr. Justin Bazan, owner and optometrist at Park Slope Eye, New York, has taken this even further by eliminating phone calls at his office entirely and is pleased with the results. This solution was based on several months of analyzing data related to phone calls, including time spent on calls and the frequency of missed calls. The team recognized that while the staff could simultaneously chat with multiple patients, they could only handle one phone call at a time.

    trends in optometry

    Chad Fleming, OD, Owner and OD at Wichita Optometry, Kansas, also identified the need for an enhanced digital presence to prioritize patient convenience. His practice faced the challenge of managing a high volume of phone calls and text messages, requiring either additional staff hiring without an immediate increase in revenue or a strategic reallocation of existing personnel.

    optometry industry trends

    Dr. Fleming optimized the patient experience by setting up automated checkouts at some of his practice locations. This approach enabled him to reassign three front desk employees to the digital communications team. While the transition required patient education to familiarize them with the virtual check-in process on iPads, it did not result in patient attrition.

    optometry industry trends

    Source

    Brianna Rhue, OD, Owner and Optometrist of West Broward Eyecare Associates, Florida, agrees that the traditional approach of answering calls and checking emails once a day differs from today’s patient expectations. She advocates step-by-step optimizations throughout the patient journey to eliminate unnecessary wait times and increase productivity.

    trends in optometry

    Upgrading to a more advanced EHR system is one of the significant opportunities to streamline practice operations, save practitioners time, money, and stress, and align with optometry industry trends. Unfortunately, once hailed as revolutionary, some widely adopted EHR solutions are now criticized for their burdensome workflows and counterintuitive interfaces. This has led some practitioners to describe their interaction with systems as “death by a thousand clicks.”

    By leveraging up-to-date EHR features like customizable patient encounter templates, integrated imaging and diagnostic tools, and patient outcome tracking, eye care professionals can shift their focus from paperwork to patient care.

    Another of optometry trends gaining momentum among optometry practice owners is offering flexible payment options. This reflects not only the growing demand for convenience but also the financial constraints of patients navigating the current economy that is heading to a recession.

    Dr. Rhue encourages practices to adopt mobile payment solutions that enable patients to pay electronically using platforms like Apple Pay, Venmo, or PayPal at the point of service. For balances due after the visit, the ability to send secure payment links via text message can greatly enhance the collection process.

    optometry trends

    Source

    Furthermore, providing patient financing options empowers patients to choose how and when they pay. This offers additional convenience for both parties and eliminates friction by allowing patients to spread the cost of their care over time rather than requiring full payment upfront.

    If you are still determining which technologies of these optometry industry trends your patients will be eager to adopt, consider the approach taken by Scott Jens, OD, the owner of Isthmus Eye Care, Wisconsin. Dr. Jens has successfully implemented post-examination surveys to gather patient feedback. This strategy serves a dual purpose: demonstrating your commitment to patient satisfaction and gaining valuable insights into which technological advancements would most benefit your practice.

    optometry trends

     

    Optometry trends in the exam room: tech-driven precision and patient education

    Optometry relies heavily on technology, and investing in hardware upgrades is a significant financial commitment. However, if your hardware needs are met, but you still want to be at the forefront of technological advancements, consider specialized software and platforms to extend the possibilities of your existing devices.

    Dr. Maria Sampalis, OD, the owner of Sampalis Eye Care, Rhode Island, utilizes two such programs in her practice. To support her specialization in dry eye management, she employs CSI Dry Eye. Additionally, she uses Altris AI, an AI-powered platform for OCT scan analysis, to provide a second opinion and enhance diagnostic accuracy.

    Dr. Sampalis finds that the Dry Eye software allows her and her staff to analyze symptoms and images comprehensively, improving patient care, time savings, and increasing diagnostic precision. See how OCT AI works here. 

    Her patients also appreciate Altris AI, which analyzes OCT scans for over 70 pathologies and biomarkers while also calculating the risk of developing glaucoma.

    optometry industry trends

    Working with specialized software solutions improves diagnostic accuracy and aids in patient education. Visual representations of their conditions, facilitated by these technologies, empower patients with a clearer understanding, leading to increased treatment compliance.

    Optometry trends

    Eye Place, an optometry center in Columbia, also leverages Altris AI, among other cutting-edge technologies. They capture images using the Topcon Maestro2 OCT and use Image Net6 software to export DICOM files to the Altris AI platform.

    trends in optometry

    Beyond AI-powered OCT analysis, Eye Place utilizes state-of-the-art diagnostic tools, such as 3D OCT equipment, to screen for serious conditions, including glaucoma, diabetes, and macular degeneration. Furthermore, they work with AdaptDX Pro, a technology capable of detecting macular degeneration earlier than traditional methods.

    Another case of optimizing and enhancing the exam process is West Broward Eyecare Associates. They implemented  Optify, a smart building solution offering full fiber connectivity. Patients can pre-select frames in the online optical store before their visit, streamlining the in-office experience. Additionally, the practice utilizes Dr. Contact Lens, a platform for convenient ordering, reordering, and prescription management for contact lens wearers, reducing paper waste.

    There are also advancements in AI transcription technology that are poised to ease clinical documentation and automate a traditionally laborious task.

    The adoption of AI in clinical documentation has been shown to reduce the time doctors spend on charting by approximately 2 hours per day. 

    AI exam transcription is still in the process, and the existing possibilities are not yet flawless—struggling with patient responses like “mm-hm” and “uh-huh”—the technology is evolving, promising greater efficiency and accuracy in the future. For example, one such program starts the transcription process of the exam by confirming patient consent and a click of the record button by the optometrist. Then, AI captures, structures, and summarizes information in real-time, filtering for relevant details to generate documentation for each patient appointment. 

    Optometry trends for competitive advantage: using AI in Marketing and Decision-making

    Some practice owners may still believe their patient demographics do not necessitate an expanded online presence, particularly when considering elders. But you should be different from your competitors.

    The reality is that today’s patients, regardless of age, are increasingly turning to the Internet for information and services. While word-of-mouth referrals remain valuable, a solid online presence is essential for practice growth and visibility in today’s competitive landscape.

    Twin Forks Optometry and Vision Therapy in New York reports that their most effective marketing strategy involves a monthly-to-quarterly newsletter distributed to existing patients. This newsletter highlights practice updates, recent vision therapy graduates, new podcast episodes, and seasonal information. They’ve also observed that educational posts generate significant engagement and have even led to new patient visits.

    optometry industry trends

    Voice Search Optimization (VSO) is emerging as one of the new trends in optometry that has the potential to benefit practices significantly. Dr. Brianna Rhue, OD, co-owner of West Broward Eyecare Associates in Florida, asserts that a search engine optimized (SEO) website alone will soon be insufficient for patients to discover your practice online easily, especially in highly competitive locations.

    Contrary to popular belief, it’s not just the tech-savvy individuals who rely on voice assistants. This technology is predominantly used by older individuals who haven’t mastered typing or face difficulties with it.

    However, while the benefits of digital communication are undeniable, it’s crucial to acknowledge that it often adds up yet another layer of responsibility to already overburdened teams. This is why generative AI tools like ChatGPT and Gemini are gaining popularity among optometrists, offering solutions to this and other challenges.

    For example, Dr. Ryan Cazares, the owner and founder of Scott Eye Care in Louisiana, utilizes ChatGPT to generate social media and educational content for his practice. He brainstorms with AI content ideas, creates visuals for social media and marketing campaigns, and has even developed a unique mascot (Dr. Seymour) that engages his audience.

    Trends in optometry

    The practitioner also uses AI to generate personalized educational materials for their patients. Traditionally, his practice relied on generic Optometric Association pamphlets, but now, it has transitioned to simple one-page educational sheets tailored to individual patient needs.

    trends in optometry

    Dr. Haley Perry, owner of Elite Eye Care, New York, provides another example of AI’s potential in practice management. Her goal for this year was to increase patient volume without expanding her staff, and ChatGPT played a pivotal role in achieving this objective. 

    Faced with the decision between two vendors for new exam room equipment, she used AI to analyze each vendor’s pricing and financing options, weigh the pros and cons of the equipment in relation to her goals, and forecast the return on investment (ROI) for each option. This analysis enabled her to select the most suitable vendor and estimate the timeframe for recouping her investment.

    Dr. Perry also leverages AI to analyze patient feedback, demographic data, and treatment outcome statistics to ensure equipment investments align with patient needs. For instance, if data reveals a high prevalence of conditions like glaucoma, AI can help justify investing in advanced glaucoma screening tools.

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    Summing up

    The optometry landscape is evolving, driven by raised patient expectations for convenience and efficiency. Practices adapt to these changes by embracing emerging optometry trends to achieve more precise diagnostics, streamline patient journeys, enhance the exam room experience, and build trust and connection. Much of this technology is AI-based, with even more advancements on the horizon. So, optometrists implementing these solutions today are poised to secure a significant competitive advantage.

     

  • How we build Ethical AI at Altris AI

    Andrey Kuropyatnyk
    03.09.2024
    13 min read

    How we build Ethical AI at Altris AI

    As the co-owner of the AI HealthTech startup, I get many questions regarding biases and the security of our AI algorithm. After all, Altris AI works directly with patients’ data, which is why these questions are inevitable and even expected. So, I decided to share our approach to building Altris AI as an ethical AI system. 

    From the very first moments of the company’s creation, I knew that AI and healthcare were two topics that had to be handled very carefully. That is why we ensured that every aspect of the AI platform creation aligned with modern security and ethics guidelines.

    It’s like building a house: you need to take care of the foundation before getting to the walls, roof, and decor. Without it, everything will fall sooner or later. Ethical principles of AI are this foundation.  

    The following aspects of Ethical AI were the most important for us: machine training ethics, machine accuracy ethics, patient-related ethics, eye care specialists-related ethics, usefulness, usability, and efficiency.

    FDA-cleared AI for OCT analysis

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    1. Machine Training Ethics

    To create an accurate algorithm capable of analyzing OCT scans, we needed to train it for years. When it comes to machine training, we speak about data for this training. There are 2 major aspects of machine training ethics that need to be discussed: data ownership and data protection

    Data ownership/Data privacy indicates authority to control, process, or access data. By default, all patients’ data belongs exclusively to patients; no one owns it and sells it to a third party. For Altris AI machine training, all the data was obtained from patients directly who voluntarily agreed to share it and signed relevant documents.

    More than that, no client’s data, under any circumstances, is used to train the Altris AI.

    Data protection

    • GDPR

    Currently, there are the following regulations to protect the confidentiality of patients’ data. The European Union (EU) has legislatures of General Data Protection Regulation (GDPR), Cybersecurity Directive, and Medical Devices Regulation.

    • HIPAA

    In the US, the Health Insurance Portability and Accountability Act (HIPAA) is suggested as a counterpart for European legislation to cover wider confidentiality issues in medical data.

    At Altris AI, we obtained EU certification and ensured that all data is GDPR and HIPAA-compliant. This also applies to all the patients’ data we receive. 

    • European Union Artificial Intelligence Act

    Provider obligations

    As a provider of a high-risk AI system, we comply with the obligations listed under Article 16.

    High-risk obligations

    Under Article 6, high-risk obligations apply to systems that are considered a ‘safety component’ of the kind listed in Annex I Section A, and to systems that are considered a ‘High-risk AI system’ under Annex III.

    At Altris AI we followed these obligations:

    • Established and implemented risk management processes according to Article 9.
    • Used high-quality training, validation, and testing data according to Article 10.
    • Established documentation and design logging features according to Article 11 and Article 12.
    • Ensured an appropriate level of transparency and provided information to users according to Article 13.
    • Ensured human oversight measures are built into the system and/or implemented by users according to Article 14.
    • Ensured robustness, accuracy, and cybersecurity according to Article 15.
    • Set up a quality management system according to Article 17.

    Transparency Obligations

    At Altris AI we also followed the transparency obligations under Article 50:

    • The AI system, the provider or the user must inform any person exposed to the system in a timely,  clear manner when interacting with an AI system, unless obvious from context.
    • Where appropriate and relevant include information on which functions are AI-enabled, if there is human oversight, who is responsible for decision-making, and what the rights to object and seek redress are.

    2. Machine Accuracy Ethics.

    Data transparency.

    Where transparency in medical AI should be sought?

    Transparency in Data Training:

    1. What data was the model trained on? Including population characteristics and demographics.

    The model’s proprietary training data set was collected from patients from several clinics who consented to share their data anonymously for research purposes. The dataset includes diverse and extensive annotated data from various OCT scanners, encompassing a range of biomarkers and diseases. It does not specifically target or label demographic information, and no population or demographic information was collected.

    2. How was the model trained? Including parameterization and tuning performed.
    The training process for the deep learning model involves several steps:

    • Data Annotation: Medical experts annotated the data, creating the ground truth for biomarker segmentation.
    • Data Preprocessing: The data is augmented using unsupervised techniques (e.g., albumentations library) to increase diversity during training.
    • Model Architecture: The model’s architecture is based on the UNet model with ResNet backbones, incorporating additional training techniques specifically engineered for OCT images.
    • Training Process: The model is trained using supervised learning techniques to predict the output biomarker segmentation mask and diagnosis label, employing backpropagation and gradient descent to minimize the loss function.
    • Parameterization: The model has millions of parameters (weights) adjusted during training. Hyperparameters such as learning rate, batch size, and the number of layers are tuned to optimize performance.
    • Tuning: Hyperparameter tuning is performed using techniques like grid search, random search, or Bayesian optimization to find the optimal set of parameters that improve the model’s performance on validation data.

    3. How has the model been trained to avoid discrimination?
    The model training uses a wide variety of data to ensure exposure to different perspectives, reducing the likelihood of reinforcing a single viewpoint. No data related to race, gender identification, or other sensitive attributes is used at any stage of the model’s lifecycle (training, validation, inference). The model solely requires OCT images without additional markers or information.

    4. How generalizable is the model? Including what validation has been performed and how do you get comfortable that it generalizes well.

    • Validation Methods: The model is validated using a variety of images that were not seen during training.
    • Performance Metrics: Metrics like Dice and F1 score are used to evaluate the model’s performance.
    • Cross-Domain Testing: The model is tested on images from different OCT scanners and time frames to ensure it can generalize well.
    • User Feedback: Real-world usage and feedback help identify areas where the model may not generalize well, allowing for continuous improvement.

    5. How explainable is the model? Including what explainability testing has been done, if any.

    Explainability Techniques: Techniques like SHAP (SHapley Additive exPlanations), GradCAM, and activation visualization are used to understand which parts of the input images the model focuses on when making predictions.

    Medical Expert Testing: Regular testing and analysis are conducted to ensure that the model’s detections make sense to medical experts and that the model’s decisions align with logical and reasonable patterns.

    Any AI system is opaque (unintelligible) for two reasons:

    • Innate complexity of the system itself.
    • Intentional proprietary design for the sake of secrecy and proprietary interests.

    Biases. In most instances, an AI tool that gives a wrong decision usually reflects biases inherent in the training data. Biases might be racial, ethnic, genetic, regional, or gender-based. 

    There should not be any bias related to race and ethnicity because there is no evidence that biomarkers and pathologies manifest themselves differently in patients of different races and ethnicities. Altris AI uses sufficiently diverse gender and age-related data to provide accurate results for OCT analysis.

    3. Patient-related ethics.

    Patient-related ethics in AI are based on the rights of beneficence, nonmaleficence (safety), autonomy, and justice. Patients exercise their rights either explicitly through informed consent or implicitly through norms of confidentiality or regulatory protections.

    Informed Consent. 

    Informed consent is based on the principle of autonomy. It could authorize the partial or complete role of algorithms in health care services and detail the process of reaching diagnostic or therapeutic decisions by machines. Clinicians should explain the details of these processes to their patients. Patients should have the choice to opt in or out of allowing their data to be handled, processed, and shared.

    As these rights can be enabled by eye care professionals, they remain on the side of eye care professionals in our case. However, eye care professionals who use Altris AI not only inform patients about using AI for OCT scan analysis but also use the system to educate patients with the help of color coding. 

    Confidentiality.

    Patients’ confidentiality is a legal obligation and a code of conduct. Confidentiality involves the responsibility of those entrusted to handle and protect patient’s data.

    All the data that is used inside the Altris AI platform is anonymized and tokenized, and only eye care professionals who work with patients see any personal information. For the Altris AI team, this data is viewed as a programming code.

    4. Eye care specialist-related ethics.

    AI systems, like Altris AI, are unable to work 100% autonomously, and therefore, eye care specialists who use them should also make ethical decisions when working with AI. 

    Overreliance on AI. One of the important aspects of physician-related ethics is overreliance on AI during diagnostic decisions. We never cease to repeat that Altris AI is not a diagnostic tool in any sense; it is a decision-making support tool. The final decision will always be made by an eye care professional. It is an eye care professional who must take into consideration the patient’s clinical history, the results of other diagnostic procedures, lab test results, concomitant diseases, and conclusions from the dialogue with the patient to make the final decision. 

    Substitution of Doctors’ Role. Considering the information mentioned above, it is important to clarify the aspect of substituting eye care specialists. It should always be kept in mind that the aim of adopting AI is to augment and assist doctors, not to replace them.

    Empathy. Empathetic skills and knowledge need to be further incorporated into medical education and training programs. AI performing some tasks offers space for doctors to utilize empathy in medical education and training.

    FDA-cleared AI for OCT analysis

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    5. Usefulness, Usability, and Efficacy. 

    According to the Coalition for Health AI (CHAI) checklist, AI in healthcare must be, first of all, useful, usable, and efficient.

    To be useful, an AI solution must provide a specific benefit to patients and/or healthcare delivery and prove to be not only valid and reliable but also usable and effective. The benefit of an AI solution can be measured based on its effectiveness in achieving intended outcomes and its impact on overall health resulting from both intended and potentially unintended uses. An assessment of benefits should consider the balance between positive effects and adverse effects or risks. 

    In the case of Altris AI, its usefulness is proved by the clients’ testimonials we receive regularly. 

    Relatedly, an effective AI solution can be shown to achieve the intended improvement in health compared to existing standards of care, or it can improve existing workflows and processes.

    With Altris AI, we make patient screening and triage faster and more effective. We also significantly improve the detection of early pathologies, such as early glaucoma, which are often invisible to the human eye. 

    Usability presupposes that the AI tool must be easy for healthcare practitioners. Altris AI is actively used by more than 500 eye care businesses worldwide, proving its usability. Moreover, we constantly collect feedback from users and improve the platform’s UI/UX.

    Conclusion

    In conclusion, Altris AI has built its platform with a strong commitment to ethical AI principles, ensuring patient data protection, transparency, and compliance with global regulations like GDPR HIPAA, EU AI Act. The system is designed to support, not replace, eye care professionals by enhancing diagnostic accuracy and improving early detection of diseases. By emphasizing machine training ethics, patient-related rights, and the usability of their AI tool, Altris AI fosters trust in healthcare technology while maintaining high standards of transparency, accountability, and human oversight in medical decision-making.

  • Optometry Technology: What to Expect? 

    optometry technology
    Maria Znamenska
    7 min.
    7 min.

    Optometry Technology: What to Expect? 

    For this article, we surveyed eye care professionals on which optometry technology appears most promising to them. The answers were divided among AI for more precise diagnostics, advanced contact lenses, and new iterations of OCTs.

    Of course, this is not the whole list of possible new tech in optometry, but these are the topics that draw the most attention today. 

    The article delves deeper into each of these technologies, as well as explores oculomics, the new way of understanding the correlation between eye pathology and overall human health.

    Explore how AI for OCT scan analysis really works

    New tech in optometry: AI for Medical Image Analysis

    AI has blossomed in recent years, transforming not only how we work and relax but also how we manage our health. It’s no surprise that our survey of professionals revealed AI as the most promising technology in optometry.

    The most immediate and practical AI implementation in optometry is the analysis of medical images, such as fundus photos and OCT scans.

    They require no additional equipment beyond the OCT and fundus cameras many practitioners already own, are cost-effective, and add huge value to a practice. 

    optometry technology

    There are many companies that detect a number of biomarkers and help with diagnostic decision-making already, and their number will only increase from year to year for several reasons:

    • AI systems for medical image analysis speed up patient triage
    • AI systems help to detect early, minor, and rare pathologies which sometimes can be missed
    • AI systems help with complex cases when a second opinion is needed
    • Quantitative analysis of biomarkers improves treatment results monitoring making it more efficient

    For instance, AI today can assess the early risk of glaucoma based on the GCC asymmetry measurements. Here is how AI-powered OCT workflow would look. 

    AI-assisted readings of OCT scans are already helping not only with pathology detection but also with the analysis of its progression or response to treatment. This represents a new approach to monitoring, where practitioners no longer need to sift through various patient notes but can directly compare reports from previous examinations and observe how, for instance, shadowing has changed in micrometers.

    technology in optometry

    AI programs are becoming even more invaluable with an aging population, as diseases prevalent in older individuals become increasingly common while ophthalmology and optometry face a shortage of specialists. This situation will transform the optometrist’s role, with AI empowering practitioners with the diagnostic capabilities to manage many conditions without referral. This will benefit patients, enabling timely routine screenings and diagnoses and preventing months-long waits that can sometimes lead to irreversible blindness.

    AI systems are also being implemented in ophthalmic trials for biomarker detection, exploring the relationship between imaging biomarkers and underlying disease pathways. For instance, a recent study linked levels of various cytokines, including VEGF, MCP-1, and IL-6, with specific OCT-derived biomarkers like fluid parameters and outer retinal integrity. 

     

    new tech in optometry

    This significantly accelerates the research process, assisting in identifying the right target audience based on OCT scans, eliminating manual data annotation, and revealing the subtlest changes, progression or regression, and patient responses during trials. 

    While material advancements allow us to build more precise machines, the new tech in optometry likely won’t involve some unheard-of device. Instead, AI software will enable us to extract the maximum potential from the technologies we already use.

    Explore how AI for OCT scan analysis really works

     

    New Tech in Optometry: New Iterations of OCT

    Even though OCTs entered the market relatively recently, they swiftly became indispensable ancillary tests in ophthalmic practice for many professionals. The primary reason is their high-quality imaging of the retina, nerve fiber layer, and optic nerve, offering a near in-vivo “optical biopsy” of the retina.

    However, the technology continues to evolve – partly due to technological advancements and partly due to the ability to extract even more data from OCT machines through sophisticated software.

    SD-OCT is undergoing continuous development, expanding its range of applications. Multimodal imaging, which combines SD-OCT with other imaging techniques like autofluorescence and angiography, now allows for improved diagnosis and management of a wider array of diseases. 

    Several prominent OCT evolutions combine technological advancements and promise widespread adoption. They are:

     

    New Tech in Optometry: En-face OCT

    En-face OCT in current systems is based on software reconstruction of OCT images. Image slices are selected retrospectively from full recorded volumes or calculated by depth projection along specific depth ranges, enabling three-dimensional data visualization in a fundus projection. This technique allows the projection of specific retinal and/or choroidal layers at a given depth onto an en-face view.

    new tech in optomery

    While we are more accustomed to working with cross-sectional images (B-scans), microstructural changes and the retinal and choroidal vasculature morphology are challenging to evaluate using B-scans alone. En-face OCT offers numerous advantages, including the ability to precisely localize lesions within specific subretinal layers using their axial location on OCT cross-sections and to register projected OCT images to other fundus imaging modalities using retinal vessels as landmarks.   

    Currently, en-face OCT is being applied to various specialized areas within the eye, encompassing the anterior segment, glaucoma, infectious diseases, and the retina.

     

    Optometry Technology: SS-OCT

    Like SD-OCT, swept-source OCT (SS-OCT) utilizes Fourier domain technology to optimize higher-quality wavelength transduction within the frequency domain. This enables rapid sweeping scan patterns across a broad bandwidth.

    However, instead of a broad-bandwidth light source projected all at once, as in SD-OCT, SS-OCT employs a single tunable laser that sweeps through different frequencies to cover the entire spectrum swiftly. The light reflected from the eye is captured by a photodetector significantly faster than the charge-coupled device (CCD) camera used in SD-OCTs. This difference translates to a faster scanning speed of up to 400,000 axial scans per second, eliminating the typical depth-dependent signal drop-off associated with SD-OCT. Additionally, the faster scanning speed reduces image distortions caused by eye movements and allows for wider B-scans, facilitating widefield imaging.

    Furthermore, many SS-OCT systems utilize a light source centered at an approximately 1050 nm wavelength, providing better tissue penetration than SD-OCT. This allows for visualization of structures like the choroid, lamina cribrosa, and structures at the anterior chamber angle. This enhanced penetration is crucial in diseases like Central Serous Chorioretinopathy, where evaluating the entire thickness of the choroid can be challenging.

    Moreover, volumetric analysis of the choroid and various pathological features can aid in monitoring the progression of Wet AMD, CSCR, and Diabetic Retinopathy, as well as assessing the response to treatments such as anti-VEGF agents, laser photocoagulation, and photodynamic therapy (PDT).

     

    Optometry Trends: OCT Angiography

    Given that many ocular diseases are associated with vascular abnormalities, the ability to visualize and quantify blood flow in the eye is crucial. Traditionally, fluorescein angiography (FA) and indocyanine green angiography (ICGA) have been used for this purpose, but these procedures require intravenous injection of contrast agents, which is not only time-consuming but may lead to allergic reactions or potentially serious side effects.   

    OCTA, on the other hand, produces high-resolution, 3D angiograms of the retinal and choroidal vascular networks, taking advantage of the eye’s unique characteristic as the only organ allowing noninvasive, direct observation of its blood vessels’ structure and function. OCTA detects blood flow using intrinsic signals to capture the location of blood vessels. While it has limitations such as insensitivity to leakage and a relatively small field of view, the development of OCTA has the potential to significantly enhance our understanding of the eye’s physiology and pathophysiology, providing depth-resolved angiographic maps of the tissue’s vascular structure down to the capillary level.

    OCTA is particularly valuable in clinical settings where pathologies like diabetic retinopathy, age-related macular degeneration, retinal vein occlusions, and macular telangiectasia are frequently encountered. These conditions often alter blood flow or the blood vessels themselves in the retina, making imaging these vessels essential for diagnosis and management.

    Wide-Field and Ultrawide-Field OCT (WF-OCT and UWF-OCT)

    While OCT is a powerful ocular imaging tool, it has traditionally been limited by a relatively narrow field of view (FOV) – typically around 20 degrees × 20 degrees. To address this limitation, two advancements have emerged:

    • Wide-field OCT (WF-OCT) with an FOV of approximately 60-100 degrees captures the retina’s mid-periphery up to the posterior edge of the vortex vein ampulla.
    • Ultrawide-field OCT (UWF-OCT) with an FOV of up to 200 degrees, mapping the far periphery of the retina, including the anterior edge of the vortex vein ampulla and beyond.

    WF-OCT provides additional information compared to routine 6-9 mm scans in conditions such as diabetic retinopathy (DR), central serous chorioretinopathy (CSCR), polypoidal choroidal vasculopathy (PCV), peripapillary choroidal neovascular membrane (CNVM), or uveitic entities. It facilitates easier visualization of anatomical details of peripheral retinal changes like ischemic areas in DR, retinal vein occlusions, or sites of retinal breaks, peripheral retinal detachment, retinoschisis, and choroidal lesions (melanoma, nevus, hemangioma, choroidal metastasis).   

    As with other OCT iterations, WF and UWF OCT will likely provide the most significant insights when routinely combined with other modalities, such as OCT angiography.

    optometry technology

     

    New Tech in Optometry: Advanced contact lenses

    In our lifetime, contact lenses have evolved from mere corrective devices to sophisticated optical instruments. There are several ways that contact lenses (CLs) continue to advance:

    • Manufacturing optimization: Automation and robotization of the process for higher precision and a shift towards a more environmentally friendly approach.
    • Design: More precise designs tailored to the wearer’s eye with the help of 3D printing.
    • Material advancements: Nanotechnology/surface modifications for improved wettability, lubricity, and antimicrobial properties. Increased focus on biomimetic design.
    • Technological advancements: Smart lenses with thin and ultra-thin transistors capable of reacting to or registering the wearer’s stress levels, glucose levels, etc.

    Let’s take a closer look at a few examples of Smart Contact Lenses (SCLs) that combine some of the characteristics mentioned earlier.

    SCLs are wearable ophthalmic devices that offer functions beyond vision correction. These devices are integrated with sensors, wireless communication components, and microprocessors to measure biological markers. They can treat ocular pathologies by delivering drugs, light, heat, and electrical stimulation, or they can aid in diagnosing. Currently, some SCLs can help manage glaucoma, cataracts, dry eye syndrome, eye infections, and inflammation. In development are lenses to treat age-related macular degeneration (AMD), diabetic retinopathy (DR), retinitis, and posterior uveitis. An artificial retina (retinal prosthesis) is in its early developmental stage, with the potential to restore vision to some degree for specific types of blindness caused by degenerative diseases.

    Scientists from the School of Medical Sciences in New South Wales have implanted epithelial stem cells (ESCs) from a healthy eye into a contact lens. This innovation has shown promise in repairing vision loss caused by a damaged cornea. In another breakthrough, scientists from Oregon State University have utilized ultra-thin transistor technology to design SCLs that can monitor the wearer’s physiological state. While this futuristic contact lens is still in the prototype phase, several biotech companies have already expressed interest in its development.

    Smart lenses also show great promise in drug delivery. One of the main challenges with eye drops is their low bioavailability (less than 5%), primarily due to high tear turnover rates, blinking, nasolacrimal drainage, non-productive absorption by the conjunctiva, and the cornea’s low permeability. Therefore, improving bioavailability by increasing the drug’s residence time on the ocular surface remains a critical research focus. 

    Additionally, drug delivery via SCLs can offer more precise dosing. With traditional eye drops, dosage accuracy relies on the patient’s ability to tilt their head and squeeze the inverted bottle correctly, leading to inconsistent application. Consequently, compliance rates for eye drops are low. In contrast, the drug delivery process with SCLs involves lenses loaded with medication for a day or several days, potentially enhancing compliance, especially for individuals accustomed to wearing contact lenses as part of their routine.

     

    optometry technology

    Just as artificial intelligence is merging with ophthalmic devices for detection and analysis, opening new possibilities, optometry trends are also venturing contact lenses into the multidisciplinary field of theranostics, which combines therapeutics and diagnostics. This field is uncovering new avenues of research, shedding light on disease mechanisms, and driving drug and medical device development. Theranostics leverages knowledge and techniques from nanotechnology, molecular and nuclear medicine, and pharmacogenetics to achieve goals such as in vitro diagnostics and prognostics, in vivo molecular imaging and therapy, and targeted drug delivery. This approach is shifting patient care towards proactive strategies and predictive treatments.

    Optometry Technology: Oculomics

    For decades, researchers have sought to measure retinal changes to identify ocular biomarkers for systemic diseases, a field now known as oculomics.

    As mentioned earlier, the eye provides a unique opportunity for direct, in vivo, and often non-invasive visualization of the neurosensory and microvascular systems:

    • The eye shares a common embryological origin with the brain, and the neurosensory retina and optic nerve are considered extensions of the brain, allowing direct observation of the nervous system.
    • Due to the length and continuity of the visual pathway, along with trans-synaptic degeneration mechanisms, damage to the central nervous system often manifests as changes in the inner retina.
    • The blood-retina barrier, similar to the blood-brain barrier, selectively allows the transport of essential substances to these metabolically active structures.
    • The aqueous and vitreous humors are plasma-derived and transport lipid-soluble substances through diffusion and water-soluble substances through ultrafiltration.
    • The lens, which grows continuously throughout life, accumulates molecules over time, providing a potential map of an individual’s molecular history.

     

    The link between the eye and overall human health is not new. However, with the increasing availability and complexity of large, multimodal ocular image datasets, artificial intelligence-based ocular image analysis shows great promise as a noninvasive tool for predicting various systemic diseases. This is achieved by evaluating risk factors, retinal features, and biomarkers. Thanks to the massive datasets generated through recent ophthalmic imaging, which are now being used for deep learning and AI training, oculomics is starting to yield more precise answers. For example, the NHS alone has been conducting eye tests for over 60 years, resulting in databases containing millions of images, complete with patient records and long-term health outcomes. These datasets have been fed into AI algorithms, leading to models that can already predict cardiovascular risk factors with accuracy comparable to the current state-of-the-art methods.

    It’s a significant opportunity because, with the aging population, a primary healthcare focus will be not only extending lifespan longevity but also maintaining crucial healthspan functions. The primary obstacles to both longevity and healthspan are chronic diseases, referred to as the “Four Horsemen of Chronic Disease” (Cardiovascular disease, Cancer, Neurodegenerative disease, and Metabolic disease). Many of these can be, if not entirely prevented, at least minimized in terms of progression through timely detection and intervention.

    One major advantage of discovering biomarkers that can predict diseases is that eye screenings are generally less intimidating than other procedures. For example, a person might regularly visit an optometrist for prescription glasses but avoid routine cervical screenings. A less anxiety-provoking and familiar procedure could significantly impact healthcare engagement. Such screenings could also make a substantial difference for chronic conditions like dementia, diabetes, and cardiovascular disease, which constitute a significant portion of the “burden of disease.”

    Explore how AI for OCT scan analysis really works

    Summing up

    Artificial intelligence has already significantly impacted our lives. It holds immense promise in optometry technology, as its primary capability—analyzing massive datasets—aligns perfectly with eye care, where thousands of images are generated daily. Training on such vast amounts of data will lead to breakthroughs in pathology and biomarker detection and their correlation with overall human health. It will enable us to take a giant leap towards proactive and predictive medicine, helping our patients live longer, healthier lives.

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  • OCT eye exam

    5 Tips When Introducing the OCT Eye Exam to Patients

    Mark Braddon
    24.07.2023
    8 min read

    As optometry technology evolves, many optometrists predict that utilizing OCT eye exam in practice will be vital in maximizing patient care. That is why successfully integrating an OCT device into your optometry practice workflow is instrumental to its clinical and commercial success.

    Optometrists from different countries often have the same questions about how to successfully integrate an OCT device into an Optometrist Practice, regardless of practice size or experience level. How to make patients feel comfortable? How to explain the importance of regular OCT scans? Will patients understand what is an OCT scan of the eye? How do we avoid patients thinking we want to perform OCT eye exams just to earn more money? The process of introducing OCT to patients is complex and covers many areas. 

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    If we speak to optometry practices, both those who are new to OCT and those who have had the OCT device for many years, most of them will want to improve the ROI and ensure the patients are gaining the full value of the OCT eye test. This article will show you 5 tips for successfully introducing the OCT eye exam to your patients.

    Remember why you invested in the OCT technology

    One may think that only novice optometrists tend to underestimate their work or do not feel confident about the value they give to patients. However, some experienced clinicians also avoid offering OCT eye tests because they think they are ‘overselling’ with additional fees for OCT, Optos, or other diagnostic exams. 

    That is why it is important to remember why you invested in OCT technology in the first place. In almost all cases, this is to improve the clinical standard of eye care that you offer to your patients. In fact, when I ask some optometrists if they want a member of their families to have an OCT eye exam, the answer is always ‘Yes, of course!’. So if you strongly recommend undergoing an examination to your relatives, why would you not recommend an OCT eye test for your patients?

    OCT eye exam

    Before a patient comes into the practice, one of the most important things you need to do is not undervalue your time, skills, and experience when charging for the additional time the OCT exam takes to interpret and discuss. 

    Implementing an OCT eye exam into regular practice improves clinical care and can generate a commercial benefit as well by increasing revenue through fees, patient retention, and loyalty. Moreover, word of mouth is often the most significant source of new patients for optometrists. If the patient feels you are confident in everything you do, it will make them more likely to recommend you to friends and family

    Explain the importance of OCT eye exam for early detection 

    From the first touch point, the patient should understand that your optometric practice takes its business seriously and provides additional diagnostic examinations, such as the OCT, to improve the quality of care. The first impression of your approach is very important, so it is crucial to start introducing the technology to the potential patient from the first point of contact. 

    As a rule, the beginning of a patient’s introduction to the OCT eye exam starts with several touch points. Whether they make their appointment for the eye examination through your website, mobile application, in person, or by phone, the most important thing you can do is create an integrated and comfortable patient journey.

    OCT eye exam

    Before a patient comes into the practice, you should explain the importance of the OCT device and its benefits compared to the standard examination. Even when the patient is fully acquainted with the OCT eye exam, they may still need help understanding why this particular imaging method is necessary. The ability of OCT eye exam to detect diseases in the early stages makes this technology indispensable for optometrists and patients and this is why it is such an excellent tool for diagnosing eye diseases. 

    More importantly, avoid frightening patients with stories about difficult-to-treat rare pathologies. Instead of talking about the pathology consequences, say that the OCT eye exam scan provides a clear map that helps locate areas of the eye with abnormalities or early changes.

    Understand the importance of a healthy-eye-as-a-baseline concept

    In this section, I want to discuss the concept of a healthy eye in more detail. When a patient comes to you for an examination, it is essential to use the correct narrative that the optometrist should use when discussing the results of an OCT eye exam with patients. It is important to emphasize that we are not looking for pathology but a healthy eye.

    We know that we will detect pathology in certain patients. The number of patients likely to have at least one pathology increases if you work with an older population. However, finding a healthy baseline scan is an important part of monitoring the long-term eye health of the patient.

    OCT eye exam

    Talking about baseline, make sure to emphasize how great it is to find a healthy eye in a patient. Explain that together you found a nice, healthy eye so you have the baseline to compare with the patient’s future scans. Emphasize that, hopefully, you will find a healthy eye at the next eye examination, but if anything does start to change, then with the help of an OCT eye exam, you will be able to detect these early and minor changes as you have the healthy baseline scan to compare to.

    It is necessary to develop your patient’s understanding through appropriate teaching and discussion. Giving the value of the baseline OCT eye exam to your patients is very important. Notice the difference between “We found nothing” and “We found a healthy eye”. The first statement is negative and undermines the reason for the scanning of patients for a healthy eye baseline. Meanwhile, the second statement is positive and clearly gives your patient more value as you have found what you are looking for.

    Integrate the OCT eye exam into the patient workflow

    Another one of my recommendations is to call the eye examination that includes the OCT eye exam the Advanced or Comprehensive Eye Examination. It is important to make sure all the staff members use the same terminology and your message to a patient is consistent from first contact to the end of the practice visit. The eye examination without the OCT exam can be called the ‘Standard Examination’ as we are not trying to make the ‘normal’ eye examination appear below standard, what we are trying to do is explain that the practice is invested in the latest technology to offer the most advanced (or comprehensive) examination for your patients benefit.

    OCT eye exam

    For example, when a patient books an appointment, make sure that the support staff uses the same terminology as written throughout the website, reminder letter/email, or mobile app if you have one.  

    When you review the OCT images with the patient, explain that you are going to look at the OCT images of the retina, which is part of the ‘Advanced examination’. When a patient pays at the end of the customer journey, make sure that the ‘Advanced Examination’ is mentioned again. When a patient rings up or books online for the next OCT eye exam, then they will understand what the ‘Advanced examination’  means and are more likely to select this option straight away for future examinations.

    Concentrate on giving more value to your patients

    Review the results with the patient to give them the actual value of an OCT scan. This will allow you to establish communication with the patient and improve their perception. Give them the “theatre” around the additional diagnostic testing so they understand how it applies to them and feel valued.

    OCT eye exam

    Remember that your knowledge, enthusiasm, and the extent to which the patient is involved in the process directly affect the clinical and commercial success. Dedicate time to each patient, involve them in the diagnostic process, and explain the OCT scans of their eyes on the screen.

    How can Altris AI help with introducing OCT Eye Exam

    OCT eye test

    When talking about improving the clinical standard of care your practice offers to your patients, the Altris AI platform can also improve the standard of care you offer to your patients. The platform helps to quickly determine if the eye is healthy. If pathology is detected, then Altris AI identifies the very early, rare, or minor changes that can be the start of something more severe. Altris AI detects over 70 pathologies and pathological signs. If early pathology is identified, then the Altris AI platform can help educate the patient by clearly highlighting the areas of concern and then giving you the opportunity to discuss lifestyle changes, over-the-counter medications, or supplements, which may help the patient now rather than just monitoring until it is time to refer. 

    The Altris AI platform can improve the patient’s understanding of the OCT exam and add value to the Advanced Eye Examination.

    OCT eye test

    All you need to do is to upload an OCT macula exam to the platform and Altris AI will assess the exam by severity differentiating the b-scans between high, medium, and low severity levels.  The segmentation/classification module will highlight pathological signs on the OCT scan one by one and give the classification/s of any pathology found to support you with the diagnosis. Meanwhile, in the Comparison module of the platform, you are able to compare the baseline scan with the current one. 

    Summing Up

    Remember why you invested in the OCT technology in the first place — usually, this is to improve the clinical standard of care you can offer to your patients. The improvement in clinical care can also generate a commercial benefit as well by increasing revenue through OCT exam fees, patient satisfaction, patient retention and loyalty, and an increase in recommendations of friends and family. 

    FDA-cleared AI for OCT scan analysis

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    Build a patient journey in such a way that, at each stage, they know that they have received a new, exciting, and, important part for the most comprehensive examination you offer. Remember that the more skill and enthusiasm you show, the more you can interest the patient and increase the probability that they will return for their next examination with OCT.

    In addition, consider using modern AI tools to help you with decision-making. Image management systems like Altris AI can help you interpret the OCT scans faster and with more confidence. This will leave more time to add value for your patient, and integrating AI into practice can be another example of how you are investing in the latest technology to benefit your patients.

  • AI for Ophthalmic clinic, photo

    Business Case: Lux Zir and AI-powered OCT Analysis in Ophthalmic Clinic

    Altris Inc.
    11.07.2023
    2 min read

    Business Case: Lux Zir and AI-powered OCT Analysis in Ophthalmic Clinic

    The Client: Lux Zir is one of the best-known ophthalmic clinics in Ukraine which provides retina diagnostics and eye treatment services. The clinic currently employs 3 full-time eye practitioners 2 general ophthalmologists and a pediatric retina expert.

    The clinic normally sees between 15-20 per day with up to 10 OCT examinations performed.

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    The Problem:

    Luxzir uses Optical Coherence Tomography as one of its core diagnostic methods because of its high level of accuracy and non-invasiveness. However, the clinic needed to solve several typical problems related to OCT.

    • Some ECPs have less experience with OCT interpretation than others and this creates an inconsistent standard of care throughout the clinic.
    • Some ophthalmologists come across complex OCT scans that they are unable to interpret without the help of their more experienced colleagues.
    • It is difficult to maintain a high standard of care for diagnostics when the CMO is absent during the period of vacation or sick leave.
    • Take out wrong and start with an inaccurate diagnosis on the basis of OCT of the patients who are referred to the clinic from other eye care centers. 

    The Solution:

    Lux Zir Ophthalmic Clinic decided to implement the Altris AI platform as they understood how it can help resolve their problems. The results have been very positive with improvements with all issues above problems, and received very positive results.

    According to Marta Shchur, Chief Medical Officer at Lux Zir clinic, the implementation of the Altris AI system improved the level of OCT diagnostics inside the clinic or if to be precise:

    • OCT interpretation is now considerably faster allowing the ECPs to see 10% more patients per day.
    • OCT diagnostics has become much more efficient: supported by Altris AI, ophthalmologists now have confidence when diagnosing pathologies and pathological signs, even rare ones.
    • The quality of diagnostics is consistent regardless of the experience of the specialists.
  • Business Case: Altris AI

    Business Case: Altris AI for Jeff Sciberras Optometry

    Altris Inc.
    10.07.2023
    1 min read

    Business Case: Altris AI for Jeff Sciberras Optometry

    The Client: Canadian Optometry Clinic

    Jeff Sciberras Optometry Clinic is an established eye care facility in Mississauga, Canada. They have been recognized as the Top Choice Optometry Clinic for the past five years running in this large Canadian city.

    Dr. Jeff Sciberras is proud of his high patient satisfaction rate: 92% of those surveyed would refer a friend, colleague, or family member to this establishment.

    Dr. Sciberras aims to provide comprehensive eye care, with a desire to utilize leading technologies and the delivery of premium eye care products.

    Recent technology investments include OCT, which allows earlier diagnosis and greater in-house management capabilities.

    AI for OCT Analysis

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    The Challenge: The optometry clinic has just purchased a brand new Optopol Revo OCT equipment and the support was needed in OCT scan interpretation. OCT is one of the most accurate methods of retina diagnostics  however, the interpretation of OCT scans can be challenging and time-consuming,  for both doctor and patient.

    The Result:

    Dr. Sciberras has been extremely satisfied with the support that the Altris AI platform provides:

    • Increased confidence when working with the new OCT device · more profound analysis of OCT scans
    • More adequate referral of complex cases.
    • Scan summaries for the patient.
    • Earning patient confidence and trust: The image of the innovative optometry center is enhanced to their patients and families.
    • The AI Segmentation/Classification Module is invaluable for the optometry center as this module helps in the identification of 70+ pathologies and pathological signs.

    The introduction of OCT with Altris AI has transformed my practice literally overnight. The integration was seamless and Altris customer support has been outstanding.

     

    Overall, Dr. Sciberras has been impressed with the experience and support Altris AI provides and is happy to have chosen to partner with them for his leading eye care center.

  • DICOM file format

    DICOM Format: Benefits of Managing DICOM images

    Mark Braddon
    31.05.2023
    6 min read

    DICOM Format: Benefits of Managing DICOM images

    DICOM file format (Digital Imaging and Communications in Medicine) was developed by the American College of Radiology (ACR) and the National Electrical Manufacturers Association (NEMA) as a standard for exchanging medical images and related information across different healthcare systems. It serves as a universal language for medical imaging, enabling interoperability between various imaging devices and systems. DICOM ensures that medical images can be exchanged and viewed consistently regardless of the manufacturer or modality.

    DICOM image format supports a broad range of medical imaging modalities, including X-ray, MRI, OCT, ultrasound, nuclear medicine, and more. It also covers related data, such as patient information, study details, image annotations, and results.

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    As the DICOM format continues to evolve to keep up with advancements in medical imaging technology, our article aims to raise awareness among ophthalmologists and optometrists about the DICOM file format.

    What is DICOM format? You can also watch a short video about DICOM and non-DICOM file formats.

    What is DICOM file format?

    Image files that adhere to part 10 of the DICOM standard are commonly known as “DICOM format files” or simply “DICOM files,” and their file extension is “.dcm.” In ophthalmology, DICOM is a widely used file format for storing and transmitting medical images. DICOM files are used to store various types of ophthalmic images as well, including retinal images, optical coherence tomography (OCT) scans, visual field tests, and angiography images.

    DICOM files consist of two main components: the header and the image data. The header contains metadata that describes the patient, study, series, and image acquisition parameters.

    DICOM image format

    This metadata includes information such as patient demographics, image acquisition parameters (e.g., imaging modality, image orientation, pixel spacing), and any annotations or measurements made on the image. The image data itself is typically stored in a compressed format, such as JPEG or JPEG 2000, within the DICOM file.

    DICOM files also support the exchange of images and associated data between different medical imaging devices and systems. This enables eye care specialists to easily share and access ophthalmic images across different platforms, such as picture archiving and communication systems (PACS), ophthalmic imaging devices, and electronic health record (EHR) systems.

    By using DICOM, ophthalmologists and optometrists can efficiently store, retrieve, and analyze ophthalmic images, ensuring accurate diagnoses and effective patient care. In the next paragraphs, we will tell you more about the benefits of the DICOM file format for eye care specialists.

     

    Benefits of DICOM format

    The DICOM standard ensures interoperability between different vendors’ OCT devices and facilitates seamless data sharing and analysis. The main difference between DICOM and other image formats is that it groups information into data sets. A DICOM file consists of several tags, all packed into a single file. It stores such info as:

    • demographic details about the patient
    • imaging study’s acquisition parameters
    • image dimensions
    • matrix size
    • color space
    • an array of additional non-intensity information necessary for accurate image display by computers.

    If you have to enter the patient’s information manually, there’s always a chance you can misspell the name or other information. However, when using a DICOM file to store patients’ information and monitor patients’ health, eye care specialists can be sure the chance of human bias is much lower.

    When you work in an optometry practice or a clinic, you may spend a lot of time filling in the details every time you upload a file. And if your clinic is busy and you do 30-50 uploads daily, it could take hours. Using DICOM image format significantly speeds up the process and reduces errors.   

    DICOM file format

    Another benefit of the DICOM image format is that the header data information is encoded within the file so that it cannot be accidentally separated from the image data. 

    DICOM files can be stored in a DICOM server or transmitted between DICOM-compliant systems using the DICOM network protocol (DICOM C-STORE or DICOMweb). DICOM SR (structure reporting) allows for the structured representation of measurement data and annotations in OCT images. It enables the storage of quantitative measurements, such as retinal thickness or optic nerve parameters, as structured data within the DICOM file.

    In addition, eye care specialists are able to manipulate the brightness of the image when using the DICOM viewing software. Some areas of an image can be increased or decreased for a better viewing and diagnostic experience.

    Is DICOM file format popular among OCT providers?

    When it comes to optical coherence tomography, many OCT device manufacturers and software providers support the DICOM standard for storing and exchanging OCT images. Some of the prominent OCT providers that offer DICOM support include:

    • Heidelberg Engineering is a well-known provider of OCT devices and software solutions for ophthalmology. They offer OCT devices like the Spectralis OCT, which supports DICOM connectivity. The DICOM capabilities of their systems enable seamless integration with PACS and other healthcare systems.
    • Carl Zeiss Meditec is a leading manufacturer of ophthalmic devices, including OCT systems. Their OCT devices, such as the Cirrus OCT, are DICOM-compatible, allowing for efficient storage and sharing of OCT images with other DICOM-compliant systems.
    • Topcon Medical Systems is another prominent provider of OCT devices. Their OCT systems, such as the Topcon 3D OCT, support DICOM connectivity, enabling interoperability with other DICOM-enabled devices and systems.
    • NIDEK offers a range of ophthalmic imaging devices, including OCT systems. Their OCT platforms, such as the NIDEK RS-3000, support DICOM, allowing for seamless integration with DICOM-compliant infrastructure, such as PACS and EHR systems.
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    These are just a few examples of OCT providers that support the DICOM standard. It’s important to note that DICOM support may vary among different models and versions of OCT devices from each manufacturer. We recommend you consult with the specific manufacturer or review their product documentation to confirm the DICOM capabilities of their OCT systems.

    Why do we recommend using DICOM file format with Altris AI?

    Modern DICOM viewer software extends beyond simple viewing. It can enhance image quality, generate additional data, take measurements, and more, and Altris AI is no exception. Using the DICOM image file gives you more opportunities within the platform.

    Such features as

    • retina layers thickness and linear measurements

    DICOM file format

    • area and volume calculations

    DICOM file format

    are only available when using the DICOM file format. This is because it contains the original image pixel data without modifying the study metadata. In case you upload an image, retina layers thickness won’t be available, as well as the measurements.

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    Another advantage of the DICOM format is that you can add patient and examination details in a few clicks by just uploading a DICOM file since this information is being pulled out automatically. 

    DICOM file format

    In the case of other image formats, when uploading an examination, you would have to manually fill in a bunch of information such as scan widths, eye type, etc.

    Considering all mentioned above, using DICOM format files saves time, increases efficiency, and gives you more opportunities within the Altris AI platform.

    Summing up

    What is DICOM format? In conclusion, the DICOM file format proves to be a valuable asset for eye care specialists. Its unique characteristics, such as grouping information into data sets and incorporating standardized tags within a single file, offer many advantages. 

    This format ensures the preservation of accurate and comprehensive data, reducing the potential for human error and minimizing the risk of data loss or misinterpretation. The DICOM file format streamlines the archival, organization, and display of images, optimizing the workflow of eye care specialists. 

    By adhering to the DICOM standard, OCT devices and software solutions ensure compatibility, interoperability, and consistent data representation across different platforms. This enables efficient communication and collaboration among healthcare professionals, enhances research capabilities, and promotes the broader use and exchange of OCT imaging data.

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    With its widespread adoption and compatibility with various medical imaging systems, DICOM empowers ophthalmologists and optometrists to provide efficient and high-quality care while promoting seamless collaboration and knowledge sharing within the field. Ultimately, the DICOM file format plays a vital role in enhancing patient care, advancing research, and fostering innovation in the field of eye care.

  • innovations in eye care

    How 7 Leading Optometry Centers Provide Innovations in Eye Care

    Maria Martynova
    08.05.2023
    9 min read

    Top modern optometry centers are not afraid of embracing effective eye care innovation. Some offer home eye tests, others create mobile apps to try on frames remotely. There are optometry centers that use artificial intelligence to empower optometrists in OCT/ fundus interpretation. We’ve collected 7 optometry centers that are using technology now to win the competition. 

    From advanced diagnostic and treatment technologies to personalized care and patient education, these centers are transforming the way clients approach and bring innovations in eye care. 

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    Optometry meets technology: AI, AR, mobile apps, and home eye tests

    Augmented Reality (AR), mobile apps, and home eye tests are emerging trends that are changing the way people receive eye care.

    • AR technology uses the camera lens on a mobile device or your PC as the method to deliver information and graphics. A user accesses an AR application, and the camera viewpoint incorporates the data directly into the perspective in real time. With AR apps for eyewear and exams, anyone can have a large selection of glasses and other services from their homes, offices, or on the go.
    • Mobile apps offer a wide range of eye care services, from information on eye health and tips for maintaining healthy vision to virtual vision screenings. Moreover, mobile apps are also used to educate both young and experienced optometrists. We strongly believe that educational mobile apps inevitably become an additional efficient tool for OCT education because they are accessible and interactive. 
    • Another one of the innovations in eye care is Home eye tests are also often enabled by digital vision testing tools. They are becoming more and more common and offer a convenient and cost-effective way to monitor vision changes.
    • As for AI use in optometry practice, it allows its users to see a broader perspective of a patient’s eye health. Incorporating AI streamlines billing procedures, expands the input of electronic health records (EHRs), optimizes claims management, and improves cash flow. AI technology can also be used in cooperation with AR assisting in the glasses selection.

    Although these innovations in optometry and ophthalmology provide more comprehensive access to eye care and improve patient engagement, many optometry practices are still hesitating to add such innovations to their routine. That is why we prepared the info about 7 famous optometry practices that are already using innovations in eye care.

    Warby Parker

    innovations in eye care

    Warby Parker started its way in 2010 when the founders of the company were students. One of them lost his glasses during a tourist trip. The cost of replacing them was so high that he spent his first semester of graduate school without them. That is why the company’s mission is to provide affordable, high-quality eyewear to consumers, while also addressing the issue of access to vision care. 

    One of Warby Parker’s unique innovations in eye care is its Home Virtual Try-On program, which allows customers to try on up to five frames at home for free before making a purchase. This program makes it easier for customers to find the perfect pair of glasses and eliminates the need for them to go to a physical store to try on frames.

    innovations in eye care

    Warby Parker also offers an online eye exam called the Virtual Vision Test. It is designed to provide customers with a convenient and affordable way to obtain a prescription for glasses or contacts from the comfort of their own homes.

    The Virtual Vision Test is a telemedicine service that uses technology to allow customers to take an eye exam using their computer or smartphone. The test is not meant to replace a comprehensive eye exam performed by an eye doctor, but rather to provide a convenient option for those who need a prescription renewal or have mild refractive errors. 

    After completing the test, the results are reviewed by a licensed ophthalmologist or optometrist, who will issue a prescription if appropriate. The customer can then use the prescription to purchase glasses or contacts from Warby Parker or any other provider.

    Lenskart

    innovations in eye care

    Lenskart is a fast-growing company of innovations in eye care in India focused on making eyewear more affordable for everyone. To achieve this goal, the company has developed a number of innovative technologies and business models, including a mobile app that allows customers to try on frames virtually and a home vision testing service that allows to check their prescriptions from the comfort of their own home.

    One special feature of the Lenskart app is the “3D Try-On” feature, which uses 3D imaging technology to create a model of the customer’s face and allows them to try on different frames virtually. This feature helps get a better sense of how a particular frame will look on a customer’s face before making a purchase.

    innovations in eye care

    Another one of Lenskart’s innovations in eye care is the Home eye test, designed to provide people with a convenient and affordable way to obtain a prescription for glasses or contact lenses. To take the Lenskart Home Eye Test, customers must first book an appointment on the company’s website or mobile app. 

    The eye test includes a visual acuity test, a color vision test, and a refractive error test. The optometrist will also check the customer’s eye health and recommend any necessary follow-up exams or treatments. After the test, the optometrist will provide a prescription, which the customer can use to purchase glasses or contacts from Lenskart or any other provider.

    SmartBuyGlasses

    innovations in eye care

    SmartBuyGlasses is an online eyewear retailer that was founded in 2006. The company is headquartered in Hong Kong, but it operates in more than 20 countries worldwide. Company’s Virtual Try-On feature is available on the website and allows customers to upload a photo of themselves and try on glasses virtually using augmented reality.

    After the website generates a 3D model of the customer’s face, they can adjust the position and size of the glasses to get a better sense of how they will look on their faces. The virtual try-on innovations in eye care also allow to share images of themselves wearing the glasses with their friends and family to get feedback on which pair looks best on them.

    innovations in eye care

    Another eye care innovation of SmartBuyGlasses is a Lens scanner app that uses advanced technology to scan the user’s current eyeglasses lenses and analyze the prescription, allowing to order a new pair of glasses online without visiting an eye doctor.

    The app works by instructing the user to place their current eyeglasses on a flat surface and position their smartphone camera above the lenses. The app then captures a series of images and uses advanced algorithms to analyze the curvature, thickness, and other factors of the lenses to determine the prescription. 

    GlassesUSA

    innovations in eye care

    GlassesUSA is an innovative and socially responsible eyewear retailer that is committed to providing quality products and services to its customers. With its focus on technology, sustainability, and social impact, GlassesUSA has become a popular choice for customers in the United States and around the world.

    One of the innovations in eye care of GlassesUSA that is worth paying attention to is a Prescription Scanner app. The app works by guiding the user through a series of steps to scan their face and eyes using their smartphone camera. It uses advanced algorithms to analyze the user’s facial features and measure the distance between their pupils, which is a crucial factor in determining the correct prescription for eyeglasses.

    innovations in eye care

    Once the scanning process is complete, the GlassesUSA app provides the user with their personalized prescription and recommendations. The app also offers a Virtual Try-On feature that allows users to see how different frames will look on their faces before making a purchase.

    Another feature is a Find-your-Frame Quiz on the website. The quiz consists of a series of questions that ask users about their face shape, personal style, and preferences for eyeglass frames, such as color, material, and shape. Based on the user’s responses, the specially designed program generates a personalized selection of eyeglasses frames that are recommended for their face shape and style preferences.

    Zenni Optical

    innovations in eye care

    Zenni Optical offers a wide range of eyewear products, including prescription glasses, sunglasses, and sports eyewear. The company offers glasses at significantly lower prices than traditional brick-and-mortar stores, which has made it a popular choice for customers.

    Company’s Virtual Try-On feature uses advanced AR technology to create a 3D model of the user’s face, allowing them to see how different frames will fit and look on them.

    innovations in eye care

    To use the Virtual Try-On innovations in eye care, users simply need to upload a photo of themselves or use their computer or smartphone camera to take a live video. This feature then maps the user’s facial features and displays a selection of eyeglasses frames that can be tried on virtually. Users can then select different frames to see how they look from different angles, and can even compare different frames side-by-side.

    The Zenni Optical Virtual Try-On is a convenient and easy-to-use tool for anyone in the market for a new pair of glasses. It allows users to see how different frames will look on their faces without the need to visit a physical store or try on multiple pairs of glasses. 

    VSP Global

    innovations in eye care

    VSP Global is a leading eyewear company that was founded in 1955 by a group of optometrists who wanted to provide affordable eye care. Today, VSP Global is a major player in the optometric industry and offers its customers a wide range of services and products.

    The company works with a network of over 40,000 eye doctors and optometrists to provide affordable and accessible eye care to its customers. VSP Global also offers other eye care services, such as telehealth consultations, on-site eye exams for businesses and schools, and a mobile eye clinic that serves underserved communities.

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    And as every company from this article, VSP Global has a strong focus on technology and innovations in eye care. The company has developed a number of proprietary technologies, including an AI-powered platform called Eyeconic that helps customers find the right eyewear.

    Eyeconic uses machine learning algorithms to analyze a customer’s facial features and suggest frames that would fit their face shape and size. VSP Global has also developed a mobile app called myVSP that allows customers to manage their vision benefits, find an eye doctor, and order contact lenses online.

    iSight+

    effective eye care innovation

    Another AI-oriented optometry center is iSight+, located in Hong Kong. iSight+ is an excellent example of how an optometric eye care center didn’t hesitate and chose to provide innovations in eye care and a more in-depth examination of the macula.

    Andy Meau. Optometrist, the owner of ISight+ Optometric Eye Care center: 


    “Altris AI will be a great tool in helping to monitor patients with existing macular diseases. I am also honored to be the first EPC in Hong Kong to provide this service.”

    In addition, the eye care center is also equipped with advanced optometric technologies, digital photography systems, and optical coherence tomography (OCT), which helps to provide the highest quality eye examination.

    Summing Up

    Optometry centers can significantly benefit from incorporating innovations in eye care, such as augmented reality, artificial intelligence, and mobile apps, into their practice. These technologies enhance the patient experience, improve diagnostic accuracy, and streamline clinical workflows.

    Moreover, the use of innovative technology can help optometry centers stay competitive in a rapidly evolving healthcare landscape. Patients are increasingly tech-savvy and expect healthcare providers to offer convenient, digital solutions that meet their needs. By embracing innovative technologies, optometry centers can attract new patients and retain existing ones, while also increasing operational efficiency and reducing costs.

    Of course, there may be concerns about the cost and complexity of integrating new technologies into an optometry practice. However, the benefits of doing so can far outweigh these potential challenges. With careful planning and implementation, optometry centers can successfully leverage AR, AI, and other innovations in eye care to enhance patient care, improve clinical outcomes, and thrive in a rapidly changing healthcare environment.

  • New technology in optometry: we asked optometrists, cover with the photo of an expert

    Future of Optometry: How will Optometry Practice Look in 2040?

    Maria Znamenska
    29.03.2023
    9 min read

    Future of Optometry: How will Optometry Practice Look in 2040?

    In the next two decades, we can expect to see a paradigm shift in the way optometry is practiced. Advances in new technology, such as AI (artificial intelligence), machine learning, and virtual and augmented reality, are expected to revolutionize how optometrists diagnose, manage, and treat eye-related problems. Optometry’s future is promising for those who are ready to embrace innovations.

    For example, smart contact lenses that can monitor blood sugar levels for diabetic patients or detect early signs of glaucoma are already in development, and they could become mainstream within the next 20 years.

    the future of optometry

    In addition to the innovations, changes in demographics will also play a significant role in shaping the future of optometry. The aging population will require more specialized eye care, particularly for conditions such as macular degeneration and cataracts, which are more prevalent in older adults. The rise of chronic diseases such as diabetes will also increase the demand for optometric services, especially in developing countries where access to healthcare is limited.

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    The future of optometry is exciting and holds great promise for patients and practitioners alike. In this article, we will explore some of the potential changes that ODs may face in the coming years based on the survey that we have conducted.

    In the next 20 years, the technology in eye care will be represented by AI and is expected to revolutionize the field in several areas. Here are some ways AI is helping in optometry:

    • Diagnosis and treatment. AI algorithms can analyze large amounts of patient data and provide accurate and fast diagnoses of eye diseases such as glaucoma, diabetic retinopathy, and age-related macular degeneration. AI could also help in designing personalized treatment plans for individual patients.
    • Screening and monitoring. AI can help specialists screen patients for eye diseases more accurately and quickly. For example, a patient could take a picture of their eyes with their smartphone, and an AI algorithm could analyze the image for signs of eye disease. AI could also help monitor the progression of eye diseases over time.

    Future of optometry

    • Enhance patient care. AI-powered tools could help ODs provide more personalized and comprehensive care to their patients. For example, the AI algorithm helps to select the most suitable eyeglasses or contact lenses for a patient based on their unique vision needs and lifestyle factors.
    • Research and development. AI could help optometrists develop new treatments for eye diseases. By analyzing large amounts of patient data, AI algorithms could identify new patterns and potential treatments for eye diseases. Enhanced by AI precision, this enables more accurate identification and quantification of biomarkers, leading to better patient stratification, treatment monitoring, and prediction of therapeutic responses.

    In addition, the implementation of AI can present various prospects for improving clinic operations, simplifying billing procedures, accelerating the input of EHRs (electronic health records), optimizing claims management, and boosting cash flow. As high-deductible health plans (HDHPs) gain popularity among employers and patients, revenue cycle management can be seamlessly integrated with AI, considering the increasing number of patients defaulting on their medical bill payments.

    future of optometry

    Although artificial intelligence is about to bring significant changes to the industry, it is important to remember that its effectiveness is limited to tasks that it has been specifically trained to perform. In contrast, AI may not perform well in areas outside its training. 

    Therefore, it is crucial to focus on enhancing ODs’ proficiency in utilizing AI instead of worrying about the possibility of job replacement. The integration of AI provides specialists with an opportunity to enhance patient outcomes on a global scale.

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    To utilize cutting-edge technologies proficiently, OD specialists must possess critical thinking skills and the ability to manage complex cases in real-time. Additionally, communication skills are essential, including cultural sensitivity, multilingualism, and familiarity with alternative communication platforms such as smartphone-based applications. These skills will be particularly important for optometry specialists in 2040.

    technology in optometry

    Overall, AI has the potential to greatly improve the accuracy and speed of diagnosing and treating eye diseases, leading to better patient outcomes and a more efficient healthcare system.The evolution of OD and MD roles

    In 2019, Richard C. Edlow, OD, claimed that nearly 20 million more routine and medical eye exams will be required in 2025 compared to 2015. That is the future of optometry that may look frightening because of the burden. The volume of surgery required for the aging US population will also increase. What is more, the number of cataract surgical procedures will also significantly increase—from 3.6 million in 2015 to 5 million in 2025. Add here the fact that the number of ophthalmologists will increase by only 2.1% in this same period. 

    Given these facts, in the not-too-distant future, ophthalmologists will need to focus on surgical procedures, while optometrists will provide more medical care.

    the future of optometry

    The field of ophthalmology must be fully prepared to meet the huge and growing demand for surgical procedures and therapeutic intravitreal injections. This brings us to the fact that the field of optometry, in turn, must be ready to manage the ever-increasing demand for medical ophthalmic services.

    The roles of OD and MD are changing. With the advent of electronic healthcare, ophthalmologists are already spending more time on the computer than providing proper patient care. The ability to use innovative technology as well as in ophthalmology, digital thought processes, and critical thinking will create new opportunities in eye care as optometrists move further towards ‘data analysis’ and away from ‘data collection.’ OD specialists must ensure that they are properly trained in new technology in optometry and its advances to enhance, not inhibit, the quality of patient care.

    technology in optometry

    It is also worth mentioning that despite the speed of new technology in optometry, the human relationship between patient and doctor remains the most powerful tool. To properly care for patients, ODs will need more than clinical skills, knowledge, or the latest technological advances. Patients need thoughtful, professional, kind, trusting, understanding, and caring optometrists.

    As technology for the eye care advances, its education will also change. There may be more need for data analysis, less need for data collection, and an increased need for interpersonal skills (such as empathy, compassion, and bedside manner).

    Future of Optometry: AI for OCT technology in optometry

    OCT has become an important diagnostic tool for the detection and treatment of various eye diseases, such as glaucoma, macular degeneration, and diabetic retinopathy. Its ability to obtain high-resolution cross-sectional images of the retina and optic nerve will broaden the horizons of technology and help optometrists detect and track changes in ocular structures that may not be visible during normal eye examination. 

    technology in optometry

    Here are some ways in which practitioners will benefit from implementing technology in the eye care:

    • Improved diagnosis. OCT provides highly detailed images of the eye’s structures, allowing ODs to detect and diagnose eye conditions much earlier than with traditional methods. In fact, OCT is also called an optical retinal biopsy. This method makes it possible to examine 18 zones of the retina and detect minor or rare pathologies. This enables optometrists to provide timely treatment and prevent further damage to the eye. 
    • Better management of eye diseases is the future of optometry. OCT allows optometrists to monitor the progression of eye diseases such as glaucoma, ARMD, and diabetic retinopathy by taking detailed retinal images. It helps to determine the severity and stage of the disease, compare images after examination with documented results, and track disease progression. Moreover, with OCT examinations, ODs can also monitor the same patient to choose the most accurate diagnosis.
    • Enhanced patient care. OCT is a noninvasive and painless procedure that is easy for patients to undergo. It uses safe laser light, avoiding all the side effects or risks. As the procedure is comfortable and effortless for both the ODs and patients, it helps to build stronger relationships by providing a less intimidating experience than other examinations.
    • Increased revenue. Optometrists who offer OCT in their practices can generate an additional revenue stream by charging for the procedure and using it to attract new patients.

    And, as OCT becomes a standard tool in optometric practice, generating vast amounts of imaging data, AI is perfectly poised to revolutionize how this data is analyzed, interpreted, and utilized to improve patient care.

    The impact of AI is already being felt in real-world optometry practices. For example, The Eye Place, an optometry center in Ohio, has successfully implemented Altris AI, an AI-powered OCT analysis system. Dr. Scott Sedlacek, the owner of The Eye Place, reports that the system has been instrumental in detecting and defining pathologies that he might have missed, leading to earlier intervention and improved patient outcomes. Patients also appreciate the color-coded images generated by the AI, which serve as an educational tool and help them understand their treatment plans better.

    new technology in optometry

    AI technology in optometry is improving diagnostic accuracy and enhancing practices’ overall efficiency. By automating tasks such as image analysis and data entry, AI frees up optometrists’ time, allowing them to focus more on patient interaction and complex decision-making. This streamlined workflow not only benefits practitioners but also improves the patient experience, making integration of AI into optometric practice not just a possibility but a new standard.

    The future of Optometry: Focusing on myopia management

    According to a survey conducted by the American Optometrists Association, nearly 70% of optometrists reported an increase in patient requests for myopia treatment in the last two years. Myopia is a rapidly growing problem worldwide. Only in the USA, it is predicted that by 2050 the number of patients will increase to 49.8%. As unfortunate as it may be, such a global epidemic of myopia will undoubtedly create an opportunity to expand the practice of specialized treatment.

    technology in optometry

    In the future, optometrists may manage myopia using a combination of approaches, and one of the most discussed is orthokeratology (ortho-K). This non-surgical approach that involves wearing specially designed contact lenses has been used to reduce the degree of myopia since the 1960s. Although this method is not new in optometry practice, many companies are still working hard to create new approaches and upgrade them. For example, two years ago, Johnson & Johnson Vision announced FDA approval of its Acuvue Abiliti Overnight Therapeutic Lenses for the management of myopia. That same year, CooperVision announced that its Procornea DreamLite night lenses for ortho-k had received the CE Mark from European regulators for slowing the progression of myopia in children and young adults. 

    Overall, the future of myopia management with new technology in optometry will likely involve a personalized, multi-faceted approach that combines various strategies to reduce the progression of myopia and improve vision.

    Game-changing contact lenses

    Research published in Advanced Materials Technologies claimed that contact lens sensors can be used to monitor many common diseases in the near future. The fact is that biomarkers in the lacrimal fluid make it possible to create diagnostic contact lenses. Such lenses would analyze these biomarkers and detect and treat systemic and ocular diseases such as diabetes, cancer, and dry eye syndrome.

    It is predicted that in the near future, lenses will be able to monitor intraocular pressure, detect glaucoma, and even create images of retinal vessels for early detection of hypertension, stroke, and diabetes. For patients with diabetes, these lenses would be incredibly useful because they measure blood glucose levels. Some companies, like Google, have already dedicated years to creating such lenses. Nowadays, scientists are even working on lenses that change color to alert about changes in glucose levels.

    New Technology in Optometry

    However, according to Advanced Intelligent Systems, one limitation of these lenses to date is that they can typically only detect one biomarker in the eye, such as glucose or lactic acid. Lenses capable of detecting multiple chemical components are predicted to be developed in the future.

    Summing up

    Predicting the exact way new technology will affect optometry practice in 20 years is challenging, as technological advancements and societal changes can rapidly alter the way healthcare is delivered. However, the widespread adoption of AI in optometry is likely to occur well before 2040, making it crucial for practices to consider integrating this transformative technology now to remain competitive and provide cutting-edge care. Nevertheless, even though AI and technology will gain popularity among eye care specialists, AI and machine learning will still be only assistants. At the same time, ODs will be responsible for diagnosis, treatment, and care. 

    Check how artificial intelligence assists in OCT interpretation

     

    This brings to the forefront the important principles of patient education, empathy, and personal contact with patients (virtue ethics). Innovations in optometry technology should allow ODs to have more personal contact and more time to improve outcomes for patients-not to improve productivity.

    In addition, optometric education will need to address these interpersonal skills so future generations of ODs are able to adequately educate patients on findings and ensure the quality of care.

    There will always be a business of health care, but the challenge for the optometric profession is for ODs to prioritize the well-being of all patients.