Free Trial

Featured This month

  • Altris AI Receives Health Canada Approval

    AI Ophthalmology and Optometry | Altris AI Altris Inc.

    Altris AI Receives Health Canada Approval, Reinforcing Its Position as a Globally Trusted AI Decision Support Platform for OCT Analysis

    Regulatory clearance marks a pivotal milestone in Altris AI’s international expansion and its mission to bring clinical-grade AI to eye care worldwide.

    10 March 2026 — Altris AI, a leading provider of AI-powered decision support for optical coherence tomography (OCT) analysis, today announced it has received approval from Health Canada | Santé Canada, Canada’s federal health regulatory authority. This clearance represents a significant step forward in the company’s global growth strategy and its commitment to meeting the highest standards of medical device safety and clinical reliability.

    For a company scaling across international markets, regulatory approvals are far more than administrative milestones — they are foundational growth enablers. Health Canada approval strengthens Altris AI’s international positioning, opens new pathways for future regulatory submissions across key markets, and delivers a clear signal to the global healthcare community: Altris AI is built for real-world clinical practice.

    The approval confirms that Altris AI’s clinical and technical validation withstands the rigorous scrutiny of Health Canada’s regulatory review process, which evaluated the platform across five critical dimensions: clinical evidence supporting efficacy and safety claims; risk management protocols; cybersecurity safeguards; quality management systems; and intended use claims. Each of these pillars reflects the standard that modern AI-driven medical devices must meet before being trusted in clinical settings.

    Altris AI’s platform serves optometrists, ophthalmologists, and pharmaceutical organizations by providing intelligent, reliable support for interpreting OCT scans — one of the most widely used diagnostic tools in eye care. By surfacing clinically relevant findings with speed and precision, Altris AI empowers clinicians to make more informed decisions, improve patient outcomes, and increase the efficiency of ophthalmic workflows.

    “This approval is external confirmation that our platform meets the standards required for medical-grade AI,” said  Maria Znamenska, Chief Medical Officer at Altris AI. “Health Canada’s review is thorough, evidence-based, and internationally respected. Receiving this clearance validates not just our technology, but the entire approach we’ve taken — building AI that clinicians can trust, in environments where accuracy is not optional.”

    The Health Canada clearance follows a broader regulatory strategy that positions Altris AI as a compliant, audit-ready platform for healthcare systems worldwide. As global regulators increasingly scrutinize AI in medical devices, early and consistent compliance across multiple jurisdictions will become a decisive competitive differentiator.

    Altris AI’s mission is to accelerate the transition of AI in eye care from innovation to infrastructure — not as a replacement for clinical expertise, but as a trusted decision-support layer that elevates the standard of care across every point of practice.

    About Altris AI Altris AI is an AI Decision Support platform for OCT analysis, designed to support optometry, ophthalmology, and pharma with clinically validated, regulatory-compliant technology. The company is committed to expanding access to intelligent eye care diagnostics globally.

  • AI in Optometry: 5 Real Applications

    ai in optometry
    AI Ophthalmology and Optometry | Altris AI Maria Znamenska
    9 min.

    Highlights: AI in optometry is revolutionizing clinical decision-making by allowing eye care professionals to analyse B-scans with greater precision, consistency, and confidence right at the point of care.

    • AI for fundus analysis is another way to automatically evaluate fundus scans in an optimized way throughout all devices.
    •  AI-driven deep learning algorithms can detect and quantify retinal and optic nerve pathologies in OCT images, enabling earlier identification of diseases such as glaucoma, age-related macular degeneration (AMD), and other retinal conditions. 
    • AI-assisted analysis enhances clinical efficiency by helping clinicians triage scans, monitor disease progression over time, and focus on clinically significant findings, rather than relying solely on manual scan reviews. 
    • Other AI-powered tools provide objective visual insights for clinicians and patients, improving the accuracy of triage and treatment monitoring and enhancing patients’ understanding of retinal health.
    • AI enables optometrists to manage more complex ocular cases in primary care, facilitating earlier detection, risk stratification, and informed referral decisions based on objective insights.
    • AI chatbots in optometry inform about eye symptoms, guide whether to seek care (urgent vs. routine), suggest possible conditions, support patients and help decide next steps, etc. Or manage eye care specialists’ daily routine.

    Introduction 

    Artificial intelligence is increasingly shaping healthcare by enhancing clinicians’ ability to interpret complex medical data and make earlier, more informed decisions. AI in optometry is especially important in OCT imaging, where it is essential to correctly interpret subtle structural changes to identify eye disorders early.

    AI for optometrists can therefore more reliably and consistently detect and track retinal and optic nerve disorders by integrating deep learning into OCT data. In routine optometric practice, risk management and referral decision-making are enhanced by converting OCT images into understandable, actionable findings.

    Discover how optometry AI tools redefine optometry by improving diagnostic accuracy, clinical efficiency, and the quality of patient care in 5 real cases.

    1. AI Decision Support for OCT Analysis

    One of the most effective AI applications in optometry is AI decision support for OCT analysis. 

    AI decision-support systems are increasingly applied to OCT imaging to assist optometrists in interpreting complex retinal and optic nerve data. Here’s one of the real cases when AI brings ultimate use to practitioners:

    Thus, AI-powered platforms like Altris use deep learning algorithms to automatically detect and quantify structural changes, highlight areas of concern, and track progression over time via an AI OCT pathology detection tool.

    By analysing patterns across large datasets of retinal scans, the system can flag subtle abnormalities that may be difficult to identify manually, segment them automatically, and provide structured, visual insights that help clinicians make more informed, consistent decisions while monitoring patient eye health. It does everything eye care specialists do, but faster, error-free, and unbiased.

    In particular, Altris AI also applies deep learning to OCT scans to automatically detect and highlight complex retinal and optic nerve changes. 

    The system quantifies abnormalities, tracks progression over time, and provides visual insights that help optometrists interpret scans more accurately and consistently, again supporting far more informed clinical decisions.

    2. AI for Fundus Analysis

    AI for Fundus Analysis is another way to automatically evaluate fundus scans in an optimized way throughout all OCT devices. Among the top 3 AI software solutions for fundus imaging, there are:

    Auroraa AI (Optomed) is an advanced artificial intelligence platform integrated with Optomed’s handheld and tabletop fundus cameras, designed to detect multiple retinal abnormalities including diabetic retinopathy, glaucoma, and age‑related macular degeneration; it provides immediate, automated screening results to support clinicians and improve early disease detection. 

    Beammed’s AI‑powered fundus cameras  pair intelligent image analysis with portable retinal imaging to enable early detection of diabetic retinopathy and other retinal conditions, leveraging deep learning algorithms to highlight pathology and help streamline screening programs.

    Cybersight AI (Orbis) offers an AI‑driven diagnostic support tool focused on interpreting fundus images to assist eye care providers in low‑resource settings and telemedicine programs, combining machine learning with expert clinical guidance to improve access to retinal disease screening globally. Here’s how fundus tool may look like:

    Such systems provide severity scores, highlight areas of concern, and track changes over time, giving clinicians objective, reproducible insights to support their decisions. Since AI can detect early signs of conditions like glaucoma, diabetic retinopathy, and age-related macular degeneration, it often spots subtle changes that are hard to see with the naked eye. 

    3. AI for Automated Visit Scheduling

    AI‑powered appointment scheduling systems are digital tools that, alongside any modern AI OCT pathology detection tool or similar, use artificial intelligence — including natural language processing (NLP), predictive analytics, machine learning, and automated communication — to handle clinical scheduling tasks usually done manually by staff. These tools can:

    • let patients self‑schedule online, by chat, voice, or text at any time,
    •  automatically confirm, remind, reschedule, or cancel appointments,
    • optimize schedules based on provider availability and patient needs, and
    • predict and prevent clinic inefficiencies such as no‑shows. 

    In essence, the system acts as a digital receptionist and smart scheduler, integrating with clinic practice management software, EHRs, and CRM systems to manage workflows seamlessly. Best EHR systems include:

    best ehr

    Elation EHR

    Elation EHR is a cloud-based electronic health record designed primarily for independent primary care practices. It focuses on simplifying clinical workflows, documentation, and patient engagement, with strong charting tools and longitudinal patient records. It’s used to help physicians deliver personalized care while reducing administrative burden.

    Epic EHR

    Epic is one of the most widely used enterprise EHR systems globally, typically implemented by large hospitals and health systems. It integrates clinical, administrative, and billing functions into a single platform, supporting everything from patient records to population health management. It’s used to coordinate care at scale and improve interoperability across departments and organizations.

    Tebra EHR

    Tebra combines electronic health records with practice management, billing, and patient communication tools, targeting small to mid-sized medical practices. It streamlines front-office and clinical operations in one system, helping practices manage scheduling, documentation, and revenue cycle efficiently.

    Nextech

    Nextech EHR is a specialty-focused EHR designed for fields like ophthalmology, dermatology, and plastic surgery. It includes tailored templates, imaging integration, and workflow tools specific to these specialties. It’s used to enhance clinical efficiency and documentation accuracy in specialized practices.

    InSync EHR

    InSync EHR is a cloud-based EHR built for behavioral health and therapy practices. It supports telehealth, scheduling, documentation, and billing, with features tailored to mental health workflows. It’s used to improve care coordination and streamline operations for therapists and behavioral health providers.

    Oracle Health EHR

    These tools are designed to improve operational efficiency, reduce administrative burden, and enhance the patient journey in healthcare settings. They offer 24/7 availability, personalized booking flows, and real-time updates, making them a powerful part of your workflow.

    ModMed EMA

    ModMed EMA (Electronic Medical Assistant) is an AI-driven, specialty-specific EHR developed by Modernizing Medicine. It uses structured data and adaptive templates to support clinical decision-making and documentation. It’s used by specialists to increase efficiency, improve outcomes, and reduce time spent on manual data entry.

    “Up to 71% of U.S. hospitals now use predictive AI technologies for scheduling and related automation.”

     

    ai in optometry infographics

    Indeed, AI in optometry for appointments, self-scheduling, and other administrative tasks can optimize routine workflows and offer a range of benefits for both opticians and their visitors. They:

    • Remove Administrative Burden

    AI takes over repetitive scheduling tasks — booking, confirmations, cancellations, preregistration, and follow‑ups — freeing front‑desk staff and nurses to focus on patient care rather than paperwork. 

     Historically, nurse managers and front‑desk staff can spend up to 40% of their day on scheduling tasks, and automating this saves hours of labour. 

    • Provide 24/7 Booking & Patient Flexibility

    Patients no longer have to call during office hours. AI scheduling tools enable self‑service booking, changes, and cancellations at any time via chatbots, voice interfaces, or online portals. 

    This has become especially crucial, as 40% of healthcare appointments are requested outside normal business hours — times when traditional phone booking is impossible. 

    • Reduce No‑Shows & Better Attendance

    Automated reminders — via SMS, email, or voice — consistently reduce no‑show rates, which can otherwise waste clinic time and revenue. Clinics using these tools have reported:

    • No‑shows dropped from 20% to as low as 7% with automated reminders.

    • In some settings, AI virtual assistants reduced missed visits by up to ~73%. 

    AI can also predict patients likely to skip visits and prompt engagement before issues arise. 

    • Enhance Resource Use

    Instead of manually guessing who should be booked and where, such AI in optometry:

    ✔ matches patients with the right clinician,

    ✔ avoids double bookings and schedule conflicts,

    ✔ spreads appointments evenly to reduce bottlenecks, and

    ✔ improves utilization of staff time and rooms. 

    AI scheduling can increase provider utilization by 15–25% and reduce wait times by 15–30%. 

    • Improve Patient Experience

    Patients appreciate convenience. Access to online or chatbot booking correlates with improved satisfaction — one study showed satisfaction scores can rise by over 20% when patients can self‑manage appointments. 

    AI also reduces inbound phone volume by 25–40%, allowing clinics to serve patients more efficiently. 

    For instance, Tele-optometry decision support that offers

    • AI pre-analyses remote exams
    • Flags cases requiring in-person referral
    • Supports non-specialist reviewers

    has the following workflow impact:

    • Scales remote care
    • Consistent quality
    •  Faster review cycles

    Used in:

    • Large optometry chains
    • Retail vision centres
    • Franchise-based practices
    • Rural clinics
    • Community health centres
    • Mobile eye clinics, etc.

    4. AI Workflow & Practice Optimization 

    So, AI-assisted OCT analysis has become helpful in retina & glaucoma screening, in follow-ups, progression tracking, and other workflows. Meaning, what happens with OCT with the help of an AI OCT pathology detection tool is helpful in many ways:

    • OCT scans are automatically analysed
    • Pathologies are flagged (fluid, thinning, progression risk, etc.)
    • Clinicians review AI output before raw scans.

    So, they get 

    • Faster exam review
    • Fewer missed subtle findings
    • Consistent interpretation across doctors, etc.

    But real-world AI applications in optometry for clinic management do not stop there: scheduling, reminders, patient triage, administrative automation, analytics, and beyond may also be supported by specific optometry AI tools. Here are a few examples.

    AI triage tools for urgent eye issues

    • AI pre-screens OCT/fundus images
    • Exams are auto-prioritized by severity
    • High-risk patients are flagged before the visit

    Workflow impact:

    • Smarter scheduling
    • Faster routing to specialists
    • Less cognitive load on staff

    Used in:

    • High-volume optometry chains
    • Tele-optometry services

    An example of AI diagnostic software for optometry and ophthalmology can be IDx-DR AI Diagnostic System for Detecting Diabetic Retinopathy.

    Automated appointment reminders 

    Automated appointment reminders are AI- or rules-based systems, not yet independent chatbots or AI assistants, that automatically notify patients about upcoming eye exams via SMS, email, WhatsApp, or voice calls, without staff involvement.

    They usually trigger:

    • 7 days before (prep + reschedule window)
    • 48–72 hours before (confirmation)
    • 24 hours or same day (final reminder)

    which makes them still a new generation of automation tools for eye care. Well-designed systems, like the majority of AI in optometry tools, support:

    • HIPAA / GDPR-compliant messaging
    • No clinical advice in reminders
    • Audit logs of sent communications
    • Opt-out controls

    This makes them safe for both routine and medical eye care appointments.

    For example: EyeCloudPro 

    But why do no-shows happen in optometry? Like in any other service sphere, there are real reasons why: 

    • Routine exams feel “non-urgent.”
    • Long booking lead times (2–6 weeks)
    • Patients forget dilation/prep requirements
    • Elderly patients miss calls or misremember dates
    • Parents forget pediatric appointments
    • No easy way to confirm or reschedule

    Across outpatient care (including optometry), automated reminders typically achieve:

    • 20–40% reduction in no-shows
    • 5–10% increase in appointment confirmations
    • Up to 30% fewer last-minute cancellations
    • 1–2 hours/day staff time saved (no manual calls)

    In optometry specifically, clinics with long routine exam cycles often see results closer to the upper end of those ranges. What automated reminders do here is directly target forgetfulness + reduce friction. No ordinary staff can do that to such an extent. But AI can.

    Therefore, by keeping patients aware, ready, and involved, automated appointment reminders help optometry clinics reduce no-show rates. Practices may increase patient flow, maximize chair time, and enhance attendance by providing timely, customized notifications through preferred channels—all without adding to the administrative burden.


    Patient communication and optometrists’ education apps

    Patient communication, as well as optometrist education systems and applications, for mobile and desktop usage, support clearer understanding, better engagement, and more consistent care delivery. 

    For example: Chatbots in Healthcare from Capacity

    capacity

    These tools help patients understand their eye health and treatment plans, while enabling optometrists to stay informed through structured education, clinical updates, and decision-support resources—improving outcomes without increasing chair time:

    • AI translates OCT findings into plain language
    • Visual overlays show “what changed” and “why it matters.”
    • Used chairside or via patient portal

    Workflow impact:

    • Better patient understanding
    • Higher treatment acceptance
    • Shorter explanation time per visit

    Used in 

    • Routine eye exams
    • OCT review appointments
    • Retina & glaucoma visits
    • Anti-VEGF treatment discussions
    • Glaucoma therapy initiation
    • Long-term monitoring plans, etc.

    Altris Education application, as an example of a unique tool specifically designed for eye care specialists’ training:

    5. Chatbots for Consultation

    A separate category is AI chatbots and virtual assistants that help with patient follow-up, education, and communication, improving day-to-day patient communication and more. With the AI Help Assistant feature, you can create an AI chatbot trained on your specific content from any platform you like. Chatbots for consultation in optometry offer clear, practical benefits for both clinics and patients:

    • 24/7 Q&A
    • Absolutely personalized follow-up instructions
    • Higher patients satisfaction rate

    Furthermore, they provide instant, 24/7 responses to the most common eye-care questions, helping patients understand symptoms, prepare for visits, and follow post-exam instructions without even waiting for staff availability. 

    Chatbots can assist with pre-consultation triage by gathering symptoms, visual complaints, and medical history, allowing optometrists to focus on higher-value clinical tasks. 

    They also improve patient engagement and adherence by delivering personalized education, reminders, and care instructions in simple, easy-to-understand language. 

    Overall, optometry chatbots dramatically reduce administrative workload, shorten response times, and support more efficient, patient-centered care while maintaining consistent communication quality.

    Types of Chatbots in Eye Care & Optometry

    agent

    1. Symptom & Triage Chatbots

    These ask users about eye symptoms, guide whether to seek care (urgent vs. routine), suggest possible conditions, and help decide next steps. Example: Ada Health

    A study published in  Eye showed that large‑language‑model‑based chatbots (e.g., ChatGPT) could answer common ophthalmology questions with high accuracy and clarity — scoring higher than alternative generative models for diagnostic and triage‑related queries (accuracy and comprehensiveness metrics showed ChatGPT did well on standard patient questions).

    Another clinical evaluation found that AI (GPT‑4) correctly identified the appropriate diagnosis among the top three options in up to 93% of ophthalmology cases and correctly assessed urgency levels in most cases — performance comparable to that of trainees. 

    2. Real‑World Chatbots for Eye Care

     The patient describes eye symptoms and uploads images (e.g., photos or OCT scans).

    An AI assistant organizes symptoms and images for review, then a real ophthalmologist chats with the patient to guide care. Key inputs here:

    • Collect symptoms in natural language
    •  Translate or clarify reports
    •  Help the clinician interpret visuals and decide next steps

    It combines AI symptom intake with real human consultation, making remote triage efficient.

    AI in optometry real chatbot examples:

    3. DocsBot AI for Optometry Services

    Practice‑focused chatbot helping clinics answer FAQs, provide pre‑appointment instructions, and automate patient engagement. Benefits:

    • Instant responses to common patient queries

    • 24/7 availability for basic information

    • Can free up staff time by handling routine communication, such as allowing self-booking, etc. 

    Patients express high satisfaction with AI self‑booking capabilities (up to 85% positive ratings).”

    Here are some more real AI chatbot applications in eye care:

    Tool / Platform Primary Focus
    DocsBot AI Patient FAQs & practice engagement 
    ThriveDesk AI AI customer support for optometry 
    Voiceflow AI Agent Custom appointment/scheduling chatbot 
    MedReception AI Manage eye exams, contact lens orders, and optical retail coordination
    OptoAI AI Assistant Knowledge and clinical support agent 
    Pod AI AI phone/communication agent  

     

    As highlighted, there is a wide array of chatbot types in optometry, ranging from patient-facing virtual assistants to AI-powered communication platforms.  

    With features such as automated appointment scheduling, pre-visit coaching, FAQ handling, 24/7 patient engagement, and basic clinical decision support, these optometry AI systems offer substantial value.

    By streamlining administrative tasks and improving patient education, these AI chatbots free up clinicians’ time to focus on direct care.

    Overall, the integration of AI-driven chatbots is revolutionizing the delivery of eye care. They enhance operational efficiency, reduce missed appointments, support timely patient triage, and improve adherence to care plans. By combining automation with intelligent decision support, AI not only optimizes clinic workflows but also elevates patient outcomes and satisfaction, marking a  transformative shift in modern optometry practice.

    Conclusion

    AI is rapidly becoming a practical and valuable tool in optometry, particularly for analysing OCT imaging. By enabling more consistent interpretation of complex retinal and optic nerve data, AI in optometry supports earlier identification of disease-related changes, more efficient triage, and improved longitudinal monitoring. 

    Beyond clinical efficiency, AI enhances patient communication by translating OCT findings into clear visual insights, supporting better understanding and engagement. As a result, optometrists are better equipped to manage more complex cases in primary care, make informed referral decisions, and deliver higher-quality, data-informed eye care—positioning AI as a meaningful complement to clinical expertise rather than a replacement.

    FAQs

    Is AI for optometry safe?

    AI in optometry is generally safe when it is properly validated, regulated, and used as a clinical support tool rather than a replacement for professional judgment. It can improve screening accuracy, enable earlier detection of eye diseases, and streamline workflows, but it also carries risks such as diagnostic errors, data privacy concerns, and bias if systems are poorly trained or over-relied upon. For safe use, optometrists must remain responsible for final decisions; patients should be informed when AI is involved; and tools should comply with medical regulations (such as FDA or CE approval) and data protection standards, such as GDPR or similar, depending on the region.

    What’s an AI OCT pathology detection tool?

    An AI OCT pathology detection tool is a software system that uses artificial intelligence to analyse optical coherence tomography (OCT) images of the eye and automatically identify signs of disease, such as macular degeneration, glaucoma, or diabetic retinopathy; it assists clinicians by highlighting abnormalities and suggesting potential diagnoses, but it is designed to support—rather than replace—professional interpretation, and its safety and effectiveness depend on proper validation, regulatory approval, and clinician oversight.

    Can AI help reduce no-shows and long wait times in an optometry practice?

    Yes. AI applications in optometry are limitless. AI can help reduce no-shows and long wait times in optometry practices by supporting appointment scheduling, reminders, and workflow optimization—such as identifying scheduling patterns, highlighting bottlenecks, and enabling more efficient patient flow—while assisting staff with better resource planning and communication.

    What can chatbots and AI assistants do for an optometry practice?

    Chatbots and AI assistants can help an optometry practice automate patient communication, streamline scheduling, and improve clinical efficiency by answering FAQs 24/7, booking and confirming appointments, sending reminders, pre-screening patients with symptom checkers, collecting medical history before visits, and triaging urgent cases. They can also support front-desk staff by handling insurance questions, guiding patients to the right services (e.g., OCT, glaucoma screening, contact lens exams), following up after visits, and reactivating inactive patients through personalized messaging. Internally, AI in optometry assistants can summarize patient data, flag high-risk cases, analyse trends in no-shows or referrals, and help with marketing automation — ultimately reducing administrative workload, improving patient satisfaction, and increasing practice revenue.

    What kinds of clinical or diagnostic support can AI provide in eye exams?

    AI can support eye exams by assisting with image review, pattern recognition, and data organization—such as highlighting features in retinal images, supporting consistency in exam review, and providing quantitative reference information—while remaining a complement to clinician judgment rather than a replacement for clinical decision-making.

    How can AI increase optical revenue and overall patient satisfaction?

    AI in optometry can increase optical revenue and patient satisfaction by helping practices streamline workflows, reduce wait times, support personalized patient communication, and enhance the in-practice experience through clearer visualization and education tools—leading to more efficient operations, improved engagement, and higher-quality service delivery.

    References:

    Luhmann, U. F. O. (2015). Innate immunity in age-related retinal degeneration. Acta Ophthalmologica. https://doi.org/10.1111/j.1755-3768.2015.0144

    https://remidio.us/solutions/teleophthalmology-telehealth/

    https://medpick.in/product/idx-dr-ai-diagnostic-system-for-detecting-diabetic-retinopathy/

    https://www.rcophth.ac.uk/academic-and-research/eye-journal/ 

    https://webeyeclinic.com/

    https://webeyeclinic.com/how-it-works/

    https://docsbot.ai/industry/optometry-services

    https://www.voiceflow.com/ai/optometrists

    https://healthus.ai/service/ai-chatbot-appointment-module/

    https://arxiv.org/abs/2511.09394

    https://ajbsr.net/data/uploads/6387.pdf

    https://www.simbo.ai/blog/the-role-of-ai-chatbots-in-revolutionizing-appointment-scheduling-and-automated-rescheduling-to-enhance-patient-convenience-and-reduce-administrative-burden-2858961/

    https://www.simbo.ai/blog/the-role-of-conversational-ai-in-revolutionizing-appointment-scheduling-and-reducing-no-show-rates-in-optometry-practices-1067939/


    https://www.simbo.ai/blog/automating-appointment-scheduling-with-ai-chatbots-reducing-no-shows-and-streamlining-patient-management-processes-2264453/

    https://www.simbo.ai/blog/how-ai-chatbots-are-transforming-appointment-scheduling-and-reducing-no-shows-in-healthcare-facilities-3576997/


    https://www.simbo.ai/blog/the-role-of-conversational-ai-in-automating-patient-appointment-scheduling-and-enhancing-healthcare-access-and-engagement-3558513/


    https://www.oscarchat.ai/blog/ai-chatbots-for-healthcare-clinics-improve-patient-support-and-appointment-scheduling/

     

popular Posted

  • Altris AI Receives Health Canada Approval

    AI Ophthalmology and Optometry | Altris AI Altris Inc.

    Altris AI Receives Health Canada Approval, Reinforcing Its Position as a Globally Trusted AI Decision Support Platform for OCT Analysis

    Regulatory clearance marks a pivotal milestone in Altris AI’s international expansion and its mission to bring clinical-grade AI to eye care worldwide.

    10 March 2026 — Altris AI, a leading provider of AI-powered decision support for optical coherence tomography (OCT) analysis, today announced it has received approval from Health Canada | Santé Canada, Canada’s federal health regulatory authority. This clearance represents a significant step forward in the company’s global growth strategy and its commitment to meeting the highest standards of medical device safety and clinical reliability.

    For a company scaling across international markets, regulatory approvals are far more than administrative milestones — they are foundational growth enablers. Health Canada approval strengthens Altris AI’s international positioning, opens new pathways for future regulatory submissions across key markets, and delivers a clear signal to the global healthcare community: Altris AI is built for real-world clinical practice.

    The approval confirms that Altris AI’s clinical and technical validation withstands the rigorous scrutiny of Health Canada’s regulatory review process, which evaluated the platform across five critical dimensions: clinical evidence supporting efficacy and safety claims; risk management protocols; cybersecurity safeguards; quality management systems; and intended use claims. Each of these pillars reflects the standard that modern AI-driven medical devices must meet before being trusted in clinical settings.

    Altris AI’s platform serves optometrists, ophthalmologists, and pharmaceutical organizations by providing intelligent, reliable support for interpreting OCT scans — one of the most widely used diagnostic tools in eye care. By surfacing clinically relevant findings with speed and precision, Altris AI empowers clinicians to make more informed decisions, improve patient outcomes, and increase the efficiency of ophthalmic workflows.

    “This approval is external confirmation that our platform meets the standards required for medical-grade AI,” said  Maria Znamenska, Chief Medical Officer at Altris AI. “Health Canada’s review is thorough, evidence-based, and internationally respected. Receiving this clearance validates not just our technology, but the entire approach we’ve taken — building AI that clinicians can trust, in environments where accuracy is not optional.”

    The Health Canada clearance follows a broader regulatory strategy that positions Altris AI as a compliant, audit-ready platform for healthcare systems worldwide. As global regulators increasingly scrutinize AI in medical devices, early and consistent compliance across multiple jurisdictions will become a decisive competitive differentiator.

    Altris AI’s mission is to accelerate the transition of AI in eye care from innovation to infrastructure — not as a replacement for clinical expertise, but as a trusted decision-support layer that elevates the standard of care across every point of practice.

    About Altris AI Altris AI is an AI Decision Support platform for OCT analysis, designed to support optometry, ophthalmology, and pharma with clinically validated, regulatory-compliant technology. The company is committed to expanding access to intelligent eye care diagnostics globally.

  • AI in Optometry: 5 Real Applications

    ai in optometry
    AI Ophthalmology and Optometry | Altris AI Maria Znamenska
    9 min.

    Highlights: AI in optometry is revolutionizing clinical decision-making by allowing eye care professionals to analyse B-scans with greater precision, consistency, and confidence right at the point of care.

    • AI for fundus analysis is another way to automatically evaluate fundus scans in an optimized way throughout all devices.
    •  AI-driven deep learning algorithms can detect and quantify retinal and optic nerve pathologies in OCT images, enabling earlier identification of diseases such as glaucoma, age-related macular degeneration (AMD), and other retinal conditions. 
    • AI-assisted analysis enhances clinical efficiency by helping clinicians triage scans, monitor disease progression over time, and focus on clinically significant findings, rather than relying solely on manual scan reviews. 
    • Other AI-powered tools provide objective visual insights for clinicians and patients, improving the accuracy of triage and treatment monitoring and enhancing patients’ understanding of retinal health.
    • AI enables optometrists to manage more complex ocular cases in primary care, facilitating earlier detection, risk stratification, and informed referral decisions based on objective insights.
    • AI chatbots in optometry inform about eye symptoms, guide whether to seek care (urgent vs. routine), suggest possible conditions, support patients and help decide next steps, etc. Or manage eye care specialists’ daily routine.

    Introduction 

    Artificial intelligence is increasingly shaping healthcare by enhancing clinicians’ ability to interpret complex medical data and make earlier, more informed decisions. AI in optometry is especially important in OCT imaging, where it is essential to correctly interpret subtle structural changes to identify eye disorders early.

    AI for optometrists can therefore more reliably and consistently detect and track retinal and optic nerve disorders by integrating deep learning into OCT data. In routine optometric practice, risk management and referral decision-making are enhanced by converting OCT images into understandable, actionable findings.

    Discover how optometry AI tools redefine optometry by improving diagnostic accuracy, clinical efficiency, and the quality of patient care in 5 real cases.

    1. AI Decision Support for OCT Analysis

    One of the most effective AI applications in optometry is AI decision support for OCT analysis. 

    AI decision-support systems are increasingly applied to OCT imaging to assist optometrists in interpreting complex retinal and optic nerve data. Here’s one of the real cases when AI brings ultimate use to practitioners:

    Thus, AI-powered platforms like Altris use deep learning algorithms to automatically detect and quantify structural changes, highlight areas of concern, and track progression over time via an AI OCT pathology detection tool.

    By analysing patterns across large datasets of retinal scans, the system can flag subtle abnormalities that may be difficult to identify manually, segment them automatically, and provide structured, visual insights that help clinicians make more informed, consistent decisions while monitoring patient eye health. It does everything eye care specialists do, but faster, error-free, and unbiased.

    In particular, Altris AI also applies deep learning to OCT scans to automatically detect and highlight complex retinal and optic nerve changes. 

    The system quantifies abnormalities, tracks progression over time, and provides visual insights that help optometrists interpret scans more accurately and consistently, again supporting far more informed clinical decisions.

    2. AI for Fundus Analysis

    AI for Fundus Analysis is another way to automatically evaluate fundus scans in an optimized way throughout all OCT devices. Among the top 3 AI software solutions for fundus imaging, there are:

    Auroraa AI (Optomed) is an advanced artificial intelligence platform integrated with Optomed’s handheld and tabletop fundus cameras, designed to detect multiple retinal abnormalities including diabetic retinopathy, glaucoma, and age‑related macular degeneration; it provides immediate, automated screening results to support clinicians and improve early disease detection. 

    Beammed’s AI‑powered fundus cameras  pair intelligent image analysis with portable retinal imaging to enable early detection of diabetic retinopathy and other retinal conditions, leveraging deep learning algorithms to highlight pathology and help streamline screening programs.

    Cybersight AI (Orbis) offers an AI‑driven diagnostic support tool focused on interpreting fundus images to assist eye care providers in low‑resource settings and telemedicine programs, combining machine learning with expert clinical guidance to improve access to retinal disease screening globally. Here’s how fundus tool may look like:

    Such systems provide severity scores, highlight areas of concern, and track changes over time, giving clinicians objective, reproducible insights to support their decisions. Since AI can detect early signs of conditions like glaucoma, diabetic retinopathy, and age-related macular degeneration, it often spots subtle changes that are hard to see with the naked eye. 

    3. AI for Automated Visit Scheduling

    AI‑powered appointment scheduling systems are digital tools that, alongside any modern AI OCT pathology detection tool or similar, use artificial intelligence — including natural language processing (NLP), predictive analytics, machine learning, and automated communication — to handle clinical scheduling tasks usually done manually by staff. These tools can:

    • let patients self‑schedule online, by chat, voice, or text at any time,
    •  automatically confirm, remind, reschedule, or cancel appointments,
    • optimize schedules based on provider availability and patient needs, and
    • predict and prevent clinic inefficiencies such as no‑shows. 

    In essence, the system acts as a digital receptionist and smart scheduler, integrating with clinic practice management software, EHRs, and CRM systems to manage workflows seamlessly. Best EHR systems include:

    best ehr

    Elation EHR

    Elation EHR is a cloud-based electronic health record designed primarily for independent primary care practices. It focuses on simplifying clinical workflows, documentation, and patient engagement, with strong charting tools and longitudinal patient records. It’s used to help physicians deliver personalized care while reducing administrative burden.

    Epic EHR

    Epic is one of the most widely used enterprise EHR systems globally, typically implemented by large hospitals and health systems. It integrates clinical, administrative, and billing functions into a single platform, supporting everything from patient records to population health management. It’s used to coordinate care at scale and improve interoperability across departments and organizations.

    Tebra EHR

    Tebra combines electronic health records with practice management, billing, and patient communication tools, targeting small to mid-sized medical practices. It streamlines front-office and clinical operations in one system, helping practices manage scheduling, documentation, and revenue cycle efficiently.

    Nextech

    Nextech EHR is a specialty-focused EHR designed for fields like ophthalmology, dermatology, and plastic surgery. It includes tailored templates, imaging integration, and workflow tools specific to these specialties. It’s used to enhance clinical efficiency and documentation accuracy in specialized practices.

    InSync EHR

    InSync EHR is a cloud-based EHR built for behavioral health and therapy practices. It supports telehealth, scheduling, documentation, and billing, with features tailored to mental health workflows. It’s used to improve care coordination and streamline operations for therapists and behavioral health providers.

    Oracle Health EHR

    These tools are designed to improve operational efficiency, reduce administrative burden, and enhance the patient journey in healthcare settings. They offer 24/7 availability, personalized booking flows, and real-time updates, making them a powerful part of your workflow.

    ModMed EMA

    ModMed EMA (Electronic Medical Assistant) is an AI-driven, specialty-specific EHR developed by Modernizing Medicine. It uses structured data and adaptive templates to support clinical decision-making and documentation. It’s used by specialists to increase efficiency, improve outcomes, and reduce time spent on manual data entry.

    “Up to 71% of U.S. hospitals now use predictive AI technologies for scheduling and related automation.”

     

    ai in optometry infographics

    Indeed, AI in optometry for appointments, self-scheduling, and other administrative tasks can optimize routine workflows and offer a range of benefits for both opticians and their visitors. They:

    • Remove Administrative Burden

    AI takes over repetitive scheduling tasks — booking, confirmations, cancellations, preregistration, and follow‑ups — freeing front‑desk staff and nurses to focus on patient care rather than paperwork. 

     Historically, nurse managers and front‑desk staff can spend up to 40% of their day on scheduling tasks, and automating this saves hours of labour. 

    • Provide 24/7 Booking & Patient Flexibility

    Patients no longer have to call during office hours. AI scheduling tools enable self‑service booking, changes, and cancellations at any time via chatbots, voice interfaces, or online portals. 

    This has become especially crucial, as 40% of healthcare appointments are requested outside normal business hours — times when traditional phone booking is impossible. 

    • Reduce No‑Shows & Better Attendance

    Automated reminders — via SMS, email, or voice — consistently reduce no‑show rates, which can otherwise waste clinic time and revenue. Clinics using these tools have reported:

    • No‑shows dropped from 20% to as low as 7% with automated reminders.

    • In some settings, AI virtual assistants reduced missed visits by up to ~73%. 

    AI can also predict patients likely to skip visits and prompt engagement before issues arise. 

    • Enhance Resource Use

    Instead of manually guessing who should be booked and where, such AI in optometry:

    ✔ matches patients with the right clinician,

    ✔ avoids double bookings and schedule conflicts,

    ✔ spreads appointments evenly to reduce bottlenecks, and

    ✔ improves utilization of staff time and rooms. 

    AI scheduling can increase provider utilization by 15–25% and reduce wait times by 15–30%. 

    • Improve Patient Experience

    Patients appreciate convenience. Access to online or chatbot booking correlates with improved satisfaction — one study showed satisfaction scores can rise by over 20% when patients can self‑manage appointments. 

    AI also reduces inbound phone volume by 25–40%, allowing clinics to serve patients more efficiently. 

    For instance, Tele-optometry decision support that offers

    • AI pre-analyses remote exams
    • Flags cases requiring in-person referral
    • Supports non-specialist reviewers

    has the following workflow impact:

    • Scales remote care
    • Consistent quality
    •  Faster review cycles

    Used in:

    • Large optometry chains
    • Retail vision centres
    • Franchise-based practices
    • Rural clinics
    • Community health centres
    • Mobile eye clinics, etc.

    4. AI Workflow & Practice Optimization 

    So, AI-assisted OCT analysis has become helpful in retina & glaucoma screening, in follow-ups, progression tracking, and other workflows. Meaning, what happens with OCT with the help of an AI OCT pathology detection tool is helpful in many ways:

    • OCT scans are automatically analysed
    • Pathologies are flagged (fluid, thinning, progression risk, etc.)
    • Clinicians review AI output before raw scans.

    So, they get 

    • Faster exam review
    • Fewer missed subtle findings
    • Consistent interpretation across doctors, etc.

    But real-world AI applications in optometry for clinic management do not stop there: scheduling, reminders, patient triage, administrative automation, analytics, and beyond may also be supported by specific optometry AI tools. Here are a few examples.

    AI triage tools for urgent eye issues

    • AI pre-screens OCT/fundus images
    • Exams are auto-prioritized by severity
    • High-risk patients are flagged before the visit

    Workflow impact:

    • Smarter scheduling
    • Faster routing to specialists
    • Less cognitive load on staff

    Used in:

    • High-volume optometry chains
    • Tele-optometry services

    An example of AI diagnostic software for optometry and ophthalmology can be IDx-DR AI Diagnostic System for Detecting Diabetic Retinopathy.

    Automated appointment reminders 

    Automated appointment reminders are AI- or rules-based systems, not yet independent chatbots or AI assistants, that automatically notify patients about upcoming eye exams via SMS, email, WhatsApp, or voice calls, without staff involvement.

    They usually trigger:

    • 7 days before (prep + reschedule window)
    • 48–72 hours before (confirmation)
    • 24 hours or same day (final reminder)

    which makes them still a new generation of automation tools for eye care. Well-designed systems, like the majority of AI in optometry tools, support:

    • HIPAA / GDPR-compliant messaging
    • No clinical advice in reminders
    • Audit logs of sent communications
    • Opt-out controls

    This makes them safe for both routine and medical eye care appointments.

    For example: EyeCloudPro 

    But why do no-shows happen in optometry? Like in any other service sphere, there are real reasons why: 

    • Routine exams feel “non-urgent.”
    • Long booking lead times (2–6 weeks)
    • Patients forget dilation/prep requirements
    • Elderly patients miss calls or misremember dates
    • Parents forget pediatric appointments
    • No easy way to confirm or reschedule

    Across outpatient care (including optometry), automated reminders typically achieve:

    • 20–40% reduction in no-shows
    • 5–10% increase in appointment confirmations
    • Up to 30% fewer last-minute cancellations
    • 1–2 hours/day staff time saved (no manual calls)

    In optometry specifically, clinics with long routine exam cycles often see results closer to the upper end of those ranges. What automated reminders do here is directly target forgetfulness + reduce friction. No ordinary staff can do that to such an extent. But AI can.

    Therefore, by keeping patients aware, ready, and involved, automated appointment reminders help optometry clinics reduce no-show rates. Practices may increase patient flow, maximize chair time, and enhance attendance by providing timely, customized notifications through preferred channels—all without adding to the administrative burden.


    Patient communication and optometrists’ education apps

    Patient communication, as well as optometrist education systems and applications, for mobile and desktop usage, support clearer understanding, better engagement, and more consistent care delivery. 

    For example: Chatbots in Healthcare from Capacity

    capacity

    These tools help patients understand their eye health and treatment plans, while enabling optometrists to stay informed through structured education, clinical updates, and decision-support resources—improving outcomes without increasing chair time:

    • AI translates OCT findings into plain language
    • Visual overlays show “what changed” and “why it matters.”
    • Used chairside or via patient portal

    Workflow impact:

    • Better patient understanding
    • Higher treatment acceptance
    • Shorter explanation time per visit

    Used in 

    • Routine eye exams
    • OCT review appointments
    • Retina & glaucoma visits
    • Anti-VEGF treatment discussions
    • Glaucoma therapy initiation
    • Long-term monitoring plans, etc.

    Altris Education application, as an example of a unique tool specifically designed for eye care specialists’ training:

    5. Chatbots for Consultation

    A separate category is AI chatbots and virtual assistants that help with patient follow-up, education, and communication, improving day-to-day patient communication and more. With the AI Help Assistant feature, you can create an AI chatbot trained on your specific content from any platform you like. Chatbots for consultation in optometry offer clear, practical benefits for both clinics and patients:

    • 24/7 Q&A
    • Absolutely personalized follow-up instructions
    • Higher patients satisfaction rate

    Furthermore, they provide instant, 24/7 responses to the most common eye-care questions, helping patients understand symptoms, prepare for visits, and follow post-exam instructions without even waiting for staff availability. 

    Chatbots can assist with pre-consultation triage by gathering symptoms, visual complaints, and medical history, allowing optometrists to focus on higher-value clinical tasks. 

    They also improve patient engagement and adherence by delivering personalized education, reminders, and care instructions in simple, easy-to-understand language. 

    Overall, optometry chatbots dramatically reduce administrative workload, shorten response times, and support more efficient, patient-centered care while maintaining consistent communication quality.

    Types of Chatbots in Eye Care & Optometry

    agent

    1. Symptom & Triage Chatbots

    These ask users about eye symptoms, guide whether to seek care (urgent vs. routine), suggest possible conditions, and help decide next steps. Example: Ada Health

    A study published in  Eye showed that large‑language‑model‑based chatbots (e.g., ChatGPT) could answer common ophthalmology questions with high accuracy and clarity — scoring higher than alternative generative models for diagnostic and triage‑related queries (accuracy and comprehensiveness metrics showed ChatGPT did well on standard patient questions).

    Another clinical evaluation found that AI (GPT‑4) correctly identified the appropriate diagnosis among the top three options in up to 93% of ophthalmology cases and correctly assessed urgency levels in most cases — performance comparable to that of trainees. 

    2. Real‑World Chatbots for Eye Care

     The patient describes eye symptoms and uploads images (e.g., photos or OCT scans).

    An AI assistant organizes symptoms and images for review, then a real ophthalmologist chats with the patient to guide care. Key inputs here:

    • Collect symptoms in natural language
    •  Translate or clarify reports
    •  Help the clinician interpret visuals and decide next steps

    It combines AI symptom intake with real human consultation, making remote triage efficient.

    AI in optometry real chatbot examples:

    3. DocsBot AI for Optometry Services

    Practice‑focused chatbot helping clinics answer FAQs, provide pre‑appointment instructions, and automate patient engagement. Benefits:

    • Instant responses to common patient queries

    • 24/7 availability for basic information

    • Can free up staff time by handling routine communication, such as allowing self-booking, etc. 

    Patients express high satisfaction with AI self‑booking capabilities (up to 85% positive ratings).”

    Here are some more real AI chatbot applications in eye care:

    Tool / Platform Primary Focus
    DocsBot AI Patient FAQs & practice engagement 
    ThriveDesk AI AI customer support for optometry 
    Voiceflow AI Agent Custom appointment/scheduling chatbot 
    MedReception AI Manage eye exams, contact lens orders, and optical retail coordination
    OptoAI AI Assistant Knowledge and clinical support agent 
    Pod AI AI phone/communication agent  

     

    As highlighted, there is a wide array of chatbot types in optometry, ranging from patient-facing virtual assistants to AI-powered communication platforms.  

    With features such as automated appointment scheduling, pre-visit coaching, FAQ handling, 24/7 patient engagement, and basic clinical decision support, these optometry AI systems offer substantial value.

    By streamlining administrative tasks and improving patient education, these AI chatbots free up clinicians’ time to focus on direct care.

    Overall, the integration of AI-driven chatbots is revolutionizing the delivery of eye care. They enhance operational efficiency, reduce missed appointments, support timely patient triage, and improve adherence to care plans. By combining automation with intelligent decision support, AI not only optimizes clinic workflows but also elevates patient outcomes and satisfaction, marking a  transformative shift in modern optometry practice.

    Conclusion

    AI is rapidly becoming a practical and valuable tool in optometry, particularly for analysing OCT imaging. By enabling more consistent interpretation of complex retinal and optic nerve data, AI in optometry supports earlier identification of disease-related changes, more efficient triage, and improved longitudinal monitoring. 

    Beyond clinical efficiency, AI enhances patient communication by translating OCT findings into clear visual insights, supporting better understanding and engagement. As a result, optometrists are better equipped to manage more complex cases in primary care, make informed referral decisions, and deliver higher-quality, data-informed eye care—positioning AI as a meaningful complement to clinical expertise rather than a replacement.

    FAQs

    Is AI for optometry safe?

    AI in optometry is generally safe when it is properly validated, regulated, and used as a clinical support tool rather than a replacement for professional judgment. It can improve screening accuracy, enable earlier detection of eye diseases, and streamline workflows, but it also carries risks such as diagnostic errors, data privacy concerns, and bias if systems are poorly trained or over-relied upon. For safe use, optometrists must remain responsible for final decisions; patients should be informed when AI is involved; and tools should comply with medical regulations (such as FDA or CE approval) and data protection standards, such as GDPR or similar, depending on the region.

    What’s an AI OCT pathology detection tool?

    An AI OCT pathology detection tool is a software system that uses artificial intelligence to analyse optical coherence tomography (OCT) images of the eye and automatically identify signs of disease, such as macular degeneration, glaucoma, or diabetic retinopathy; it assists clinicians by highlighting abnormalities and suggesting potential diagnoses, but it is designed to support—rather than replace—professional interpretation, and its safety and effectiveness depend on proper validation, regulatory approval, and clinician oversight.

    Can AI help reduce no-shows and long wait times in an optometry practice?

    Yes. AI applications in optometry are limitless. AI can help reduce no-shows and long wait times in optometry practices by supporting appointment scheduling, reminders, and workflow optimization—such as identifying scheduling patterns, highlighting bottlenecks, and enabling more efficient patient flow—while assisting staff with better resource planning and communication.

    What can chatbots and AI assistants do for an optometry practice?

    Chatbots and AI assistants can help an optometry practice automate patient communication, streamline scheduling, and improve clinical efficiency by answering FAQs 24/7, booking and confirming appointments, sending reminders, pre-screening patients with symptom checkers, collecting medical history before visits, and triaging urgent cases. They can also support front-desk staff by handling insurance questions, guiding patients to the right services (e.g., OCT, glaucoma screening, contact lens exams), following up after visits, and reactivating inactive patients through personalized messaging. Internally, AI in optometry assistants can summarize patient data, flag high-risk cases, analyse trends in no-shows or referrals, and help with marketing automation — ultimately reducing administrative workload, improving patient satisfaction, and increasing practice revenue.

    What kinds of clinical or diagnostic support can AI provide in eye exams?

    AI can support eye exams by assisting with image review, pattern recognition, and data organization—such as highlighting features in retinal images, supporting consistency in exam review, and providing quantitative reference information—while remaining a complement to clinician judgment rather than a replacement for clinical decision-making.

    How can AI increase optical revenue and overall patient satisfaction?

    AI in optometry can increase optical revenue and patient satisfaction by helping practices streamline workflows, reduce wait times, support personalized patient communication, and enhance the in-practice experience through clearer visualization and education tools—leading to more efficient operations, improved engagement, and higher-quality service delivery.

    References:

    Luhmann, U. F. O. (2015). Innate immunity in age-related retinal degeneration. Acta Ophthalmologica. https://doi.org/10.1111/j.1755-3768.2015.0144

    https://remidio.us/solutions/teleophthalmology-telehealth/

    https://medpick.in/product/idx-dr-ai-diagnostic-system-for-detecting-diabetic-retinopathy/

    https://www.rcophth.ac.uk/academic-and-research/eye-journal/ 

    https://webeyeclinic.com/

    https://webeyeclinic.com/how-it-works/

    https://docsbot.ai/industry/optometry-services

    https://www.voiceflow.com/ai/optometrists

    https://healthus.ai/service/ai-chatbot-appointment-module/

    https://arxiv.org/abs/2511.09394

    https://ajbsr.net/data/uploads/6387.pdf

    https://www.simbo.ai/blog/the-role-of-ai-chatbots-in-revolutionizing-appointment-scheduling-and-automated-rescheduling-to-enhance-patient-convenience-and-reduce-administrative-burden-2858961/

    https://www.simbo.ai/blog/the-role-of-conversational-ai-in-revolutionizing-appointment-scheduling-and-reducing-no-show-rates-in-optometry-practices-1067939/


    https://www.simbo.ai/blog/automating-appointment-scheduling-with-ai-chatbots-reducing-no-shows-and-streamlining-patient-management-processes-2264453/

    https://www.simbo.ai/blog/how-ai-chatbots-are-transforming-appointment-scheduling-and-reducing-no-shows-in-healthcare-facilities-3576997/


    https://www.simbo.ai/blog/the-role-of-conversational-ai-in-automating-patient-appointment-scheduling-and-enhancing-healthcare-access-and-engagement-3558513/


    https://www.oscarchat.ai/blog/ai-chatbots-for-healthcare-clinics-improve-patient-support-and-appointment-scheduling/

     

  • Altris becomes the winner of VSP Vision Challenge at Vision Expo

    AI Ophthalmology and Optometry | Altris AI Altris In

    ORLANDO, FL — Altris, an IMS for OCT analysis with ROU AI models, has been named the Judge’s Winner of the 2026 VSP Vision Innovation Challenge, one of the eyecare industry’s most prestigious startup competitions. The award was presented live on March 13, 2026, on the Innovation Stage at Vision Expo inside the Orange County Convention Center in Orlando, Florida.

    Produced by RX and The Vision Council in collaboration with VSP Vision™, the 2026 VSP Vision Innovation Challenge drew applications from companies around the globe — more than half of which were venture-backed, collectively representing over $300 million in funding. After a rigorous selection process, Altris AI was chosen as one of four finalists and participated in an intensive four-week startup bootcamp before delivering a live pitch to a distinguished panel of industry judges.

    Judges recognized Altris for its clinical impact, technological sophistication, and potential to fundamentally transform the eyecare experience. The judging panel represented a diverse cross-section of industry leaders, including executives, clinicians, and investors.

    “Winning the VSP Vision Innovation Challenge is a powerful validation of what we’re building at Altris AI. Our mission is to put the most advanced retinal intelligence in the hands of every eye care professional — and this recognition from a world-class panel of judges confirms that the industry is ready for this transformation.”

    Altris AI CEO, Andrey Kuropyatnyk

    About Altris

    Altris AI serves as a “second set of eyes” for eye care specialists, identifying more than 70 retinal biomarkers from optical coherence tomography (OCT) scans ( AI models are used for Research Use Only). The platform enables providers to match patients to the most appropriate treatments, devices, and clinical trials with objective, data-driven precision. Altris system is FDA-cleared and HIPAA-compliant, and integrates seamlessly with OCT scanners from nine major manufacturers.

    By combining advanced deep learning algorithms with a clinically intuitive interface, Altris AI reduces diagnostic variability, supports earlier detection of sight-threatening conditions, and frees eye care professionals to focus on what matters most: patient outcomes.

    About the VSP Vision Innovation Challenge

    The VSP Vision Innovation Challenge is a global competition designed to source, support, and accelerate early-stage startups and technologies advancing the eyecare experience. This year’s finalists represented a broad spectrum of innovation — from AI-driven diagnostics and exam automation to digital education and accessibility-focused smart solutions.

    In addition to pitching live, finalists exhibited at Vision Expo’s Innovation Center, a dedicated emerging-technology destination featuring more than 20 next-generation startups spanning AI, augmented and virtual reality, and advanced diagnostics.

    “Innovation in eyecare is accelerating, which is why it’s crucial for the industry to stay actively engaged. We launched the VSP Vision Innovation Challenge to connect emerging technologies with the stakeholders they aim to serve, and this year is no exception. We’re proud to support solutions that advance care for both providers and patients.”

    — Will Flanagan, Head of VSP Global Innovation Center Programs and Partnerships

    Looking Ahead

    With this recognition, Altris AI continues to accelerate its mission of making retinal AI accessible to every eye care professional. The company will leverage the visibility and industry connections gained from the challenge to deepen partnerships with providers, expand clinical integrations, and advance its platform’s capabilities.

    The next VSP Vision Innovation Challenge will take place at Vision Expo 2027, scheduled for March 10–13 in Las Vegas. Applications are expected to open later this fall.

    About Altris Inc.

    Altris AI is a clinical-grade SaaS platform that empowers eye care specialists with AI-driven retinal analysis. By identifying 70+ retinal biomarkers from OCT scans, Altris AI helps providers deliver more precise, evidence-based care. The platform is FDA-approved, HIPAA-compliant, and compatible with OCT devices from nine leading manufacturers.

  • AI Ophthalmology and Optometry | Altris AI Altris Inc.

    Altris AI Receives Health Canada Approval, Reinforcing Its Position as a Globally Trusted AI Decision Support Platform for OCT Analysis

    Regulatory clearance marks a pivotal milestone in Altris AI’s international expansion and its mission to bring clinical-grade AI to eye care worldwide.

    10 March 2026 — Altris AI, a leading provider of AI-powered decision support for optical coherence tomography (OCT) analysis, today announced it has received approval from Health Canada | Santé Canada, Canada’s federal health regulatory authority. This clearance represents a significant step forward in the company’s global growth strategy and its commitment to meeting the highest standards of medical device safety and clinical reliability.

    For a company scaling across international markets, regulatory approvals are far more than administrative milestones — they are foundational growth enablers. Health Canada approval strengthens Altris AI’s international positioning, opens new pathways for future regulatory submissions across key markets, and delivers a clear signal to the global healthcare community: Altris AI is built for real-world clinical practice.

    The approval confirms that Altris AI’s clinical and technical validation withstands the rigorous scrutiny of Health Canada’s regulatory review process, which evaluated the platform across five critical dimensions: clinical evidence supporting efficacy and safety claims; risk management protocols; cybersecurity safeguards; quality management systems; and intended use claims. Each of these pillars reflects the standard that modern AI-driven medical devices must meet before being trusted in clinical settings.

    Altris AI’s platform serves optometrists, ophthalmologists, and pharmaceutical organizations by providing intelligent, reliable support for interpreting OCT scans — one of the most widely used diagnostic tools in eye care. By surfacing clinically relevant findings with speed and precision, Altris AI empowers clinicians to make more informed decisions, improve patient outcomes, and increase the efficiency of ophthalmic workflows.

    “This approval is external confirmation that our platform meets the standards required for medical-grade AI,” said  Maria Znamenska, Chief Medical Officer at Altris AI. “Health Canada’s review is thorough, evidence-based, and internationally respected. Receiving this clearance validates not just our technology, but the entire approach we’ve taken — building AI that clinicians can trust, in environments where accuracy is not optional.”

    The Health Canada clearance follows a broader regulatory strategy that positions Altris AI as a compliant, audit-ready platform for healthcare systems worldwide. As global regulators increasingly scrutinize AI in medical devices, early and consistent compliance across multiple jurisdictions will become a decisive competitive differentiator.

    Altris AI’s mission is to accelerate the transition of AI in eye care from innovation to infrastructure — not as a replacement for clinical expertise, but as a trusted decision-support layer that elevates the standard of care across every point of practice.

    About Altris AI Altris AI is an AI Decision Support platform for OCT analysis, designed to support optometry, ophthalmology, and pharma with clinically validated, regulatory-compliant technology. The company is committed to expanding access to intelligent eye care diagnostics globally.

  • Drusen on OCT: Detection, quantification, and tracking

    AI Ophthalmology and Optometry | Altris AI Maria Znamenska
    5 min.

    Introduction

    Drusen remains one of the main biomarkers of age-related macular degeneration (AMD). They play a prognostic role and reflect the stage of the disease. Distinguishing drusen parameters provides a personalized risk profile for the transition to geographic atrophy or neovascular AMD. Everyone working with AMD patients should know how to detect, quantify, and track drusen on OCT.

    What are the types of drusen?

    Drusen are accumulations of pathological material of lipid-protein nature, localized under the PES. They reflect impaired transport and exchange between the retinal pigment epithelium and Bruch’s membrane. Historically, they are divided into hard, soft, reticular pseudodruses (or subretinal drusenoid deposits) and other less common types (confluent, pachidruses) as well as other retinal OCT biomarkers for drusen segmentation.

    Hard drusen

    On ophthalmoscopy, they are small, rounded, clearly delineated foci of yellowish-white color. On OCT, they look like local deposits of hyperreflective material under the PES with a diameter of no more than 63 microns. In small quantities (up to 8), they are not a sign of pathology. They are asymptomatic in most patients.

    Soft drusen

    Soft drusen are larger than hard drusen and appear as extensive foci with blurred edges on the fundus. On OCT, they are dome-shaped and elevated above the PES and are divided into medium (63-125 μm) and large (more than 125 μm) in size. They are more strongly associated with AMD progression, especially when accompanied by pigmentary abnormalities and other OCT biomarkers (hyperreflective foci, destruction of the ellipsoidal zone, etc.). Soft drusen can enlarge and merge. An area of ​​merging drusen with a diameter exceeding 350 μm is called a drusenoid detachment of the PES.

    Soft drusen highlighted

    Soft drusen detected by Altris IMS. AI models are for Research Use Only. Not for use in diagnostic purposes. 

    Confluent drusen

    These are multiple small deposits under the PES, which can occur in relatively young patients; on FAG they often show a “starry sky” appearance. On OCT, there are multiple small symmetrical elevations of the PES, small in diameter (like hard drusen), but more numerous, prone to merging. The course is variable: some patients maintain a stable course for years, some have an increased risk of complications and transition to the late stages of AMD.

    Reticular pseudodrusen (or subretinal drusenoid deposits)

    They differ fundamentally in their localization, being located above the PES (in the subretinal space). They contain some common proteins with soft drusen, but differ in lipid composition. Due to their close location to the important photoreceptor layer, they are more often combined with a decrease in visual function, and also carry a higher risk of progression to late AMD (especially characterized by a rapid transition to geographic atrophy (GA) and the development of macular neovascularization (MNV) type 3).

    What are the levels of drusen?

    The AREDS size classification is still useful in clinical practice: small <63 μm, medium 63–124 μm, large ≥125 μm. Analyses confirm that the 5-year risk of progression to late AMD increases with the number and size of drusen in both eyes and especially with the presence of reticular pseudodrusen. In the NICE guidance for the management of patients with AMD (2018), the risk of progression also depends on the size and type of drusen, as well as the presence of associated pathological changes (pigmentary abnormalities, vitelliform deposits).

    The OCT era has added powerful quantitative metrics with AI for drusen measurement and monitoring:

    • drusen height (μm),
    • area (mm²),
    • volume (mm³),
    • topography (central ring within 1.5 mm; parafovea 3–5 mm),
    • dynamics of changes and associated biomarkers (hyperreflective foci, ellipsoidal zone disruption, presence of hypertransmission zones, etc.).

    A practically significant increase in the volume of drusen in the macular region over a year/two correlates with structural and functional deterioration (destructive changes in the photoreceptor layer, changes in ONL thickness, visual acuity). Data from multicenter projects (such as MACUSTAR) confirm the repeatability of measurements and the possibility of comparison between devices, provided that the correct algorithms are used.

    What do drusen look like on OCT?

    On B-scan OCT, classic hard and soft drusen are localized deposits of hyperreflective material between the PES and Bruch’s membrane (under the PES). Reflectivity can be uniform or heterogeneous depending on the structure and stage of development. Reticular pseudodruses are localized between the photoreceptor layer and the PES (above the PES) – this is the key difference from conventional drusen. On OCT images, they appear as tubercles in the subretinal space that remodel the outer layers of the retina (in particular, the ellipsoidal zone), and on en face, they are visualized as punctate structures, usually connected in a mesh pattern.

    A: Soft drusen. B: Hard drusen (Source) Another classic white and black scan

    In addition to the drusen themselves, clinically significant are hyperreflective foci, destruction of the ellipsoidal zone, thinning of the outer layers/ONL, formation of hyperreflective foci in OCT or geographic atrophy with the effect of hypertransmission – it is the combinations of these features that form prognostic models of the transition of intermediate AMD to late stages. The combination of these biomarkers consistently exceeds single morphometric thresholds.

    En Face Optical Coherence Tomography Illustration

    En Face Optical Coherence Tomography Illustration of the Trizonal Distribution of Drusen and Subretinal Drusenoid Deposits in the Macula (Source)

    As we can see, en face and linear OCT scans help to differentiate different types of drusen and track their progression dynamics. Modern deep learning models for AI drusen examination and en face analysis, like Altris.AI, reliably detect and segment classic drusen from subretinal drusenoid deposits, improving repeatability and reporting speed. You may see the difference from the classic white and black image analysis here:

    Confluent drusen are highlighted in red

    Confluent drusen are highlighted by Altris IMS. AI models are used for Research Use Only. Not for use in Diagnostic Purposes. 

    How to measure drusen size?

    Here we can find how drusen are measured:

    1) Classical size scale (AREDS):

    Orientation on diameter or equivalent on planar reconstructions: <63, 63–124, ≥125 μm. Convenient, but does not take volume/height or topography into account.

    2) Quantitative OCT analysis of PES elevation:

    On ZEISS CIRRUS instruments, the Advanced RPE Analysis module automatically calculates the area and volume of PES elevation in standard 3 and 5 mm rings around the fovea; the minimum height that the system consistently includes in quantitative results is about 19–20 μm. This provides repeatable metrics and a common “language of numbers” for clinical and research purposes.

    3) Morphometric rule for differentiation of drusen and drusenoid detachment of PES:

    By basal width: <350 μm – drusen, ≥350 μm drusenoid detachment of PES.

    4) AI segmentation and 3D morphometry:

    Deep networks segment Bruch’s membrane, PES, and ellipsoidal zone, as well as PES elevation on OCT, calculating drusen height/area/volume and generating dynamics maps. Validation work in 2023–2025 will demonstrate robustness between different OCT devices, which is critical for multicenter networks. Besides, you may track drusen progression on OCT AI tool and stay informed ahead of time to prevent more severe pathology changes in advance.

    Can drusen exist without macular degeneration?

    Yes, and this is possible in the following cases.

    Small (<63 μm) single drusen may occur in the elderly in the absence of other signs of AMD and concomitant risk biomarkers (hyperreflective foci, ellipsoidal zone abnormalities). In this phenotype, the 5-year risk of progression is low; routine monitoring at an interval of 1 time per year is sufficient, if possible, with recording quantitative indicators on OCT (volume/area of ​​PES elevation) for comparison in dynamics. The patient should be informed that the fact of “small drusen” alone does not equal a diagnosis of AMD and does not require treatment, but it is advisable to maintain lifestyle modification (blood pressure control, smoking cessation, a healthy diet).

    Confluent drusen are sometimes found in younger patients; they do not always fit into the classic models of AMD. Tactics – individual observation with an emphasis on high-quality OCT documentation (the same scan and control of concomitant biomarkers). In the absence of “red flags”, a 6-12 month follow-up interval is sufficient.

    Understanding Macular Degeneration

    Understanding Macular Degeneration (Source)

    Hereditary dystrophies (EFEMP1-related; associated phenotypes are Doyne’s cellular degeneration of the retina and Leventis’ malady) form drusen-like deposits without the typical pathogenesis inherent in AMD. They have an autosomal dominant inheritance pattern and are characterized by yellow-white deposits, like drusen, accumulating under the PES, often in the peripapillary zone. The clinical picture may include gradual vision loss, impaired contrast sensitivity, or metamorphopsia. In this case, timely detection of the phenotype (age of onset, family history, symmetry, characteristic fundus appearance) and referral for medical and genetic counseling with a subsequent individual follow-up plan, including monitoring of possible complications (neovascularization, atrophic changes).

    Drusen vs. drusenoid detachment of PES

    Drusen are local elevations of PES above Bruch’s membrane due to deposits of pathological material under PES. Usually multiple, of different diameters, with a tendency to merge with the formation of larger, topographically continuous areas of PES elevation.

    Drusenoid detachment of the pigment epithelium is formed from a larger conglomerate of drusenoid material, which in turn is formed as a result of the fusion of drusen.

    Another differentiating drusen and drusenoid deposits subtypes on multimodal imaging samples

    Another differentiating drusen and drusenoid deposits subtypes on multimodal imaging samples

    On B-scan OCT, it has smooth edges, uneven reflectivity, and often retains communication with neighboring drusen. On en face visualization, a conglomerate of elevation is visible, which corresponds to the zone of changes in the PES-Bruch’s membrane complex. In the absence of fluid inside the lesion, we are talking about drusenoid detachment of PES; if homogeneous hyporeflectivity is visualized under PES, this is serous detachment of PES, and if there are signs of a neovascular membrane according to OCTA or FAG, this is fibrovascular detachment of PES. Therefore, in doubtful cases, it is advisable to add OCTA to exclude hidden MNV.

    The main morphometric rule: basal width ≥350 μm (in the horizontal projection of the OCT slice favors drusenoid detachment of PES. In some situations, we also pay attention to the content (serous/optically empty space, signs of vascularization), PES profile, and associated biomarkers, since PES detachment is more often associated with the risk of transition to HA or the formation of neovascularization.

    What is the best treatment for drusen?

    Drusen are not treated as a separate nosology. They are a structural biomarker of AMD, and also have prognostic value for assessing the further development and rate of progression of the disease.

    Optimal tactics for detecting drusen:

    Optimal tactics for detecting drusen may include the following

    Risk modification: 

    • smoking cessation,
    •  blood pressure control,
    • metabolic profile,
    • diet.

    Dietary supplements based on AREDS 2: 

    • taking antioxidant complexes (lutein, zeaxanthin, vitamins C and E, zinc, copper) reduces the risk of transition to late AMD by approximately 25% within 5 years (according to AREDS 2).

    Quantitative monitoring on OCT: 

    • record the volume/area/height of drusen and their dynamics, distinguish between drusen types, detect other concomitant signs of AMD progression (hyperreflective foci, destructive changes in the ellipsoidal zone, pigmentary anomalies, vitelliform material deposition, signs of formation of foci of geographic atrophy).
    • Individualize observation intervals (depending on the type of drusen, the dynamics of their structural changes and other risk factors).
    • Among the new promising methods of treating dry AMD at the drusen stage is multiwavelength photobiomodulation.

    Multiwavelength photobiomodulation:

    This method is aimed at stopping or regressing the progression of dry AMD by modulating mitochondrial activity and consists of the use of specific light (red and near-infrared spectrum from ~590 to 850 nm), which can reduce oxidative stress in retinal cells, inflammation and apoptosis of PES cells.

    The efficacy as a potential treatment approach has remained controversial until recently: studies have shown only temporary improvement in visual function and reduction in drusen volume (not maintained for 6 months).

    Updated data from the LIGHTSITE III study were presented at the ARVO 2025 conference. They showed that photobiomodulation can significantly slow the decline in visual acuity and reduce the rate of expansion of HA zones

    Recently, the FDA approved photobiomodulation for the treatment of AMD.

    For complications:

    • Neovascular AMD– anti-VEGF.
    • Geographic atrophy – injectable drugs (inhibitors of the C3 and C5 complement system), approved by the FDA

    The role of AI drusen quantification OCT

    The role of AI: automated drusen-volume measurement in OCT is now a reality. IT allows automated segmentation and counting (3D volume, area, height), identification of reticular pseudodruses and other signs of AMD, and compilation of prognostic profiles.

    In practice, applying an OCT drusen-counting algorithm reduces variability in assessments and helps personalize visit frequency. Additionally, home OCT monitoring models with AI analysis are being developed, indicating that broader AI support for AMD is fast approaching.

    Conclusion

    Drusen on OCT are more than just a sign of AMD. They have become one of the most important biomarkers of age-related macular degeneration and a kind of “compass” in the daily practice of an ophthalmologist. Today we understand that:

    Drusen come in different types, and, accordingly, carry different prognostic information: hard, soft, confluent, and reticular pseudodrusen. Each type carries a different risk and requires a different surveillance strategy.

    Drusen levels are no longer limited to diameter, height, volume, dynamics, and structural features as well as accompanying OCT biomarkers have also become important. It is the combination of these parameters that allows us to predict the transition to the late stages of AMD.

    OCT has changed the game: drusen can now be seen in 3D, segmented automatically, build PES elevation maps, and compare data between visits. Thanks to this, the doctor receives a lot of information about the evolution of the disease.

    AI sets a new standard: algorithms can accurately calculate drusen volume, identify their subtypes, generate prognostic profiles, and reduce interobserver variability. This translates data from subjective descriptions into objective, reproducible numbers.

    Drusen classification on OCT using AI allows not only ascertaining the presence of drusen, but also differentiating their type, objectively measuring their number and parameters, and tracking their dynamics via AI drusen quantification on OCT. For the doctor, this means identifying risk factors in the early stages of retinal disease, accurately comparing data between visits, and prescribing the correct therapy promptly.

    Home monitoring is the future that has already begun: the first FDA-approved solutions with “OCT + AI” are currently used to monitor fluid in neovascular AMD, but they pave the way for daily structural monitoring of drusen as well. This means that in the near future, the patient may be able to monitor their own retina at home, and the doctor may be able to see the dynamics in real time.

    In the treatment of drusen wet or dry AMD, the main goal remains not to “remove drusen,” but to minimize risks (smoking, diet, systemic factors), prescribe AREDS2-based complexes, timely detect complications, and apply already available therapies (anti-VEGF in INM, C3 and C5 inhibitors of the complement system in HA). Among the new promising methods for treating dry AMD at the drusen stage is multiwavelength photobiomodulation.

     

    It is important to remember when communicating with the patient: drusen is not a therapeutic target, but a structural “compass”. We do not “treat drusen.” Instead, we systematically reduce risks (smoking, blood pressure, nutrition), use drugs based on the AREDS2 formula, and most importantly, we regularly measure their quantitative parameters in dynamics. When complications appear and the transition to a late stage occurs, we prescribe treatment based on the same objective OCT metrics. Thus, instrumental accuracy and AI analytics turn drusen into a manageable marker that helps to timely detect the risks of AMD progression.

    Thus, drusen on OCT have become a bridge between morphology and prognosis. They provide an opportunity to build a long-term strategy for preserving vision. Today, the doctor is required not only to see drusen, but also to quantitatively measure, assess in dynamics, calculate the risk, and explain to the patient his individual risks. It is thanks to these approaches that we are moving towards a new paradigm – personalized ophthalmology, where decisions are made based on objective digital data, enhanced by artificial intelligence.

    Sources:

      1. https://pubmed.ncbi.nlm.nih.gov/39558093/
      2. https://jamanetwork.com/journals/jamaophthalmology/fullarticle/2765650
      3. https://link.springer.com/article/10.1007/s00417-024-06389-x
      4. https://iovs.arvojournals.org/article.aspx?articleid=2804052
      5. https://www.ophthalmologyscience.org/article/S2666-9145(25)00182-4/fulltext
      6. https://www.nature.com/articles/s41433-024-03460-z
      7. https://www.ophthalmologytimes.com/view/arvo-2025-update-on-the-lightsite-iii-study-in-amd
  • Central Retinal Vein Occlusion CRVO OCT: Detection and Modern Approaches to Monitoring and Treatment

    crvo
    AI Ophthalmology and Optometry | Altris AI Maria Znamenska
    3 min.

    Introduction

    Central Retinal Vein Occlusion (CRVO) OCT is one of the most common and clinically significant vascular disorders affecting the eye, often resulting in substantial visual impairment. This condition ranks second among causes of vision loss due to vascular disease, after diabetic retinopathy, placing a considerable burden on both healthcare systems and patients’ quality of life. Epidemiological studies show that the prevalence of RVO increases with age, and in populations with concomitant cardiovascular disease, the risk of developing occlusion rises severalfold.

    Despite a long history of study, it is the breakthroughs in instrumental diagnostics over the past decade that have fundamentally changed our approach to recognizing and managing RVO. Previously, assessment of the macula and retinal vasculature relied primarily on ophthalmoscopy. While still an important tool, it has inherent limitations.

    Optical coherence tomography (OCT) has revolutionized diagnostic standards. With its high resolution and ability to capture subtle structural changes within the retinal layers, OCT has become indispensable for determining disease severity, monitoring treatment efficacy, and conducting long-term follow-up. It allows for the detection of minimal early signs of edema, subclinical structural damage, and initial manifestations of ischemia—changes that were practically inaccessible for dynamic assessment 10–15 years ago.

    This level of precision is particularly critical for patients at increased risk of RVO. The most vulnerable groups include individuals with arterial hypertension, diabetes mellitus, glaucoma, coagulation disorders, as well as older adults, in whom the vascular walls may already have undergone degenerative or sclerotic changes.

    Importantly, modern RVO treatments require objective dynamic monitoring. OCT enables precise evaluation of structural changes, tracking of therapeutic response, and individualization of treatment strategies, helping to avoid both overtreatment and undertreatment.

    Thus, the role of OCT today goes far beyond simple visualization: it is a key tool for prognostic assessment, patient stratification, optimization of therapeutic decisions, and timely detection of complications.

    crvo

    1. What RVO Is and Why It Occurs?

    Central Retinal Vein Occlusion (CRVO) OCT is a disruption of venous blood outflow in the retina due to partial or complete vein occlusion. As a result, the following occur:

    • Blood stasis
    • Increased venous pressure
    • Impaired capillary perfusion
    • Retinal edema, especially in the macular area
    • Risk of neovascularization

    Early detection is critical, as prompt treatment—particularly for macular edema—significantly increases the chances of preserving or restoring vision. Delayed diagnosis can lead to progression of ischemia, neovascularization, neovascular glaucoma, and persistent macular dysfunction.

    RVO also has important systemic implications: patients with a history of RVO have a higher risk of acute cardiovascular events (myocardial infarction, stroke, heart failure) compared with the general population. This emphasizes the need for comprehensive management, involving not only ophthalmologists but also other specialists, such as cardiologists.

    Central vs. Branch Retinal Vein Occlusion: Pathogenesis Differences

    • Central Retinal Vein Occlusion (CRVO) occurs when blockage happens at the level of the lamina cribrosa. Compression, arterial wall thickening, or thrombotic processes disrupt blood outflow from the entire retina. Typical signs include:
      • Diffuse hemorrhages
      • Marked macular edema
      • Increased risk of optic disc and iris neovascularization due to severe ischemia
      • Generally worsen prognosis than branch occlusions
    • Branch Retinal Vein Occlusion (BRVO) usually occurs at arteriovenous crossings, where a thickened artery compresses a vein, causing localized occlusion. Characteristic features include:
      • Localized edema and hemorrhages
      • Clear segmental distribution
      • Prognosis is generally better than that of CRVO, though macular edema may persist

    Key Risk Factors for RVO

    Modern studies and guidelines identify the following as the main risk factors:

    • Arterial hypertension
    • Atherosclerosis and age-related vascular changes
    • Diabetes mellitus (even without diabetic retinopathy)
    • Glaucoma and elevated IOP
    • Hypercoagulable states, thrombophilia
    • Obstructive sleep apnea
    • Age >50 years

    Rare cases of RVO associated with thromboembolic complications after COVID‑19 infection or vaccination have also been reported, highlighting the ongoing relevance of thrombotic mechanisms.

    Impact on Microcirculation and Vision

    RVO leads to:

    • Impaired normal venous outflow
    • Sharp elevation of hydrostatic venous pressure
    • Damage to the blood-retinal barrier
    • Leakage of plasma and cellular elements into the retinal interstitium, causing macular edema
    • Development of ischemic zones
    • Over time, thinning of inner retinal layers, neuroepithelial atrophy, and damage to the photoreceptor layer

    These changes are best assessed with OCT, which enables precise patient stratification and treatment planning. Timely diagnosis, proper monitoring, and early therapy are essential.

    fluid progression

    2. OCT Signs of Retinal Vein Occlusion: Detecting Subtle Changes

    With the advent of OCT, detection of structural retinal changes in RVO has significantly improved—even at early stages without obvious clinical signs.

    Acute Stage Changes (first weeks after occlusion)

    • Macular edema:
      • Cystic spaces in inner retinal layers (INL, OPL)
      • Increased central retinal thickness
      • Subretinal fluid (serous neurosensory detachment)
    • Intraretinal hemorrhages: appear on OCT as hyperreflective areas with shadowing of underlying layers
    • Ischemia indicators:
      • Hyperreflectivity of neuroepithelium
      • Cotton-wool spots

    Chronic Stage Changes (months later)

    • Chronic ischemic and atrophic changes (thinning of inner retinal layers)
    • Disruption of photoreceptor layer (ELM and EZ)
    • Disorganization of inner retinal layers (DRIL)
    • Persistent edema (>6 months) indicates chronic RVO requiring therapeutic adjustment

    AI for OCT thus allows both acute diagnosis and long-term monitoring of ischemic progression or tissue remodeling.

    tissues

    rvo

    crvo

    3. Assessment of Macular Changes in RVO Using OCT

    Central retinal vein occlusion crvo OCT is now considered the gold standard for diagnosing, monitoring, and assessing treatment response in macular edema, including that associated with RVO.

    OCT is highly sensitive for:

    • Quantitative and qualitative analysis (central retinal thickness [CRT], macular volume [MV], size and number of cystic spaces, DRIL, photoreceptor layer integrity)
    • Evaluating treatment response
    • Detecting minimal residual cysts
    • Predicting visual acuity outcomes

    Typical OCT Findings in RVO:

    • Diffuse retinal thickening
    • Cystoid macular edema (localized cysts deforming normal retinal architecture)
    • Serous neurosensory detachment (indicative of blood-retinal barrier breakdown)
    • Disruption of EZ and ELM (photoreceptor involvement, critical for final visual acuity)

    These capabilities make OCT an integral part of modern RVO monitoring.

    rvo 2

    4. Top 3 Challenges in RVO OCT Analysis

    Despite its power, OCT assessment of RVO has significant limitations:

    1. Need for normative comparison
      Interpretation requires comparison with the patient’s contralateral eye or established normal values. Systemic vascular anomalies can affect both eyes, limiting standardization.
    2. Complexity with comorbidities
      Many RVO patients have systemic (hypertension, diabetes) or ophthalmic comorbidities (diabetic retinopathy, AMD, glaucoma, epiretinal membrane), complicating interpretation. It can be difficult to distinguish RVO-related changes from combined pathology.
    3. Requirement to consider the clinical context
      OCT provides only part of the clinical picture. Accurate interpretation requires integration of symptoms, medical history, systemic factors, fundoscopic findings, and other diagnostic tests. Anatomical variations, comorbidities (glaucoma, cataract), and individual treatment response also necessitate a personalized approach.

    5. Treatment of RVO: Modern Approaches

    Currently, no treatment restores normal retinal venous circulation. Therefore, therapy focuses on controlling complications, primarily macular edema and preventing neovascularization (retinal, iris/optic disc, neovascular glaucoma, hemorrhages, and tractional changes).

    All RVO patients should receive systemic management, ideally in collaboration between an ophthalmologist and a cardiologist or internist. Monitoring of blood pressure, lipids, glucose, and coagulation factors is essential, as RVO often signals systemic vascular risk.

    Treatment decisions must be individualized, considering:

    • RVO subtype (CRVO vs. BRVO)
    • Edema severity
    • Clinical and OCT findings
    • Risk of adverse effects
    • Patient status (comorbidities, ability for regular follow-up)

    Anti-VEGF Therapy as First-Line Treatment

    Intravitreal anti-VEGF injections are the first-line therapy for macular edema associated with RVO. These drugs reduce vascular endothelial growth factor (VEGF) expression, lowering vascular permeability, fluid leakage, edema, and inhibiting pathological neovascularization.

    Commonly used agents:

    • Ranibizumab, Aflibercept, Faricimab: proven safe and effective for CRVO and BRVO-related macular edema brvo vs crvo oct; studies show significant improvements in best-corrected visual acuity (BCVA) and central macular thickness (CMT).
    • Bevacizumab: used off-label for macular edema and neovascularization.

    Long-term studies indicate anti-VEGF therapy provides sustained visual improvement for many patients, with injection frequency often decreasing over time.

    Advantages:

    • High efficacy for macular edema
    • Good tolerability and safety (systemic complications are rare)
    • Personalized treatment possible

    Limitations / Challenges:

    • Some patients respond insufficiently
    • Requires frequent injections (clinic visits, financial burden, potential complications, patient discomfort)
    • Chronic or refractory edema may require alternative or combination approaches

    Steroid Implants and Injections: Second-Line Therapy

    Dexamethasone intravitreal implant (OZURDEX) is approved for RVO-related macular edema, particularly when:

    • Anti-VEGF therapy is insufficient
    • Frequent injections are impractical (distance, transportation, cost)

    Steroids reduce inflammation, vascular permeability, and fluid accumulation, useful in chronic or resistant edema.

    Risks / Limitations:

    • Cataract (especially with repeated or long-term use)
    • Increased intraocular pressure (IOP), potential steroid-induced glaucoma

    Laser Therapy

    • Panretinal photocoagulation is effective for neovascularization.
    • Its use has declined with anti-VEGF availability, which offers strong anatomical and functional results.

    Surgical Approaches

    • Vitrectomy may be considered in selected cases.
    • Surgery carries risks and is reserved for situations where other treatments fail or are inappropriate.

    Combination Strategies

    • In practice, clinicians often combine anti-VEGF therapy with steroid implants or laser treatment, depending on disease course.
    • This can reduce total injection burden, minimize side effects, and improve outcomes in chronic or recurrent edema.

    Monitoring Frequency

    • Active macular edema or ongoing treatment requires regular OCT follow-up to evaluate therapeutic response and adjust injection intervals.
    • OCT schedule:
      • Monthly at treatment initiation
      • Individualized intervals using Treat-and-Extend protocols
      • Structural monitoring to prevent atrophic changes
    • Ischemic RVO patients have the highest neovascularization risk within the first 90 days; monthly monitoring during the first 6 months is critical.

    Conclusions and Recommendations

    RVO is a complex, multifactorial vascular disorder that can cause sudden and severe vision loss, particularly in patients with systemic risk factors. Modern management aims not only to address acute complications but also to control long-term structural retinal changes.

    OCT has transformed RVO care by providing:

    • Early detection of edema, subclinical ischemia, and architectural changes
    • Dynamic monitoring of treatment response, allowing timely adjustments and optimization
    • Improved long-term prognostication through evaluation of macular thickness, outer retinal layers, and fluid volume

    OCT helps identify edema type and secondary changes—atrophy, photoreceptor damage, inner retinal thinning—allowing a more accurate visual prognosis, especially in ischemic RVO.

    When combined with modern anti-VEGF agents, long-acting steroid implants, and personalized dosing regimens, OCT enables:

    • Reduction of unnecessary injections via interval optimization
    • Maximized treatment efficacy based on morphological findings
    • Prevention of recurrence and progression through early detection of edema

    Thus, OCT is not merely a visualization tool but a core element of clinical decision-making, improving patient management, preventing complications, and enabling more complete and stable visual recovery.

    Clinical Recommendation: Integrate regular OCT assessments into RVO management, with attention to macular thickness dynamics and outer retinal layer integrity for precise disease control and optimized therapeutic outcomes.

    References:

    1. https://pubmed.ncbi.nlm.nih.gov/38714470/
    2. https://www.rcophth.ac.uk/wp-content/uploads/2015/07/Retinal-Vein-Occlusion-Guidelines-Executive-Summary-2022.pdf
    3. https://www.mdpi.com/2077-0383/14/4/1183
    4. https://www.auctoresonline.org/article/clinical-therapeutic-orientation-in-retinal-venous-obstruction
    5. https://www.mdpi.com/2077-0383/10/3/405
    6. https://pmc.ncbi.nlm.nih.gov/articles/PMC10801953
    7. https://www.mdpi.com/2075-4418/13/19/3100
    8. https://karger.com/oph/article-abstract/242/1/8/255831/Microvascular-Retinal-and-Choroidal-Changes-in?redirectedFrom=fulltext
    9. https://link.springer.com/article/10.1007/s40123-024-01077-9
    10. https://pubmed.ncbi.nlm.nih.gov/39717563/
    11. https://provider-rvo.vision-relief.com/introduction/management/

     

  • Key Trends in Ophthalmology and Optometry in 2026

    trends
    AI Ophthalmology and Optometry | Altris AI Maria Znamenska
    3 min.

    Introduction

    The year 2026 in ophthalmology will not be defined by a single “major breakthrough,” but rather by key trends in Ophthalmology and optometry in 2026, and the maturation of several directions whose discoveries and innovations are now transitioning into everyday clinical practice. While just a few years ago innovations were often perceived as isolated technologies far removed from real-world care (a new drug, device, or piece of equipment), today entire ecosystems are being formed: from early detection to long-term monitoring, from the ophthalmologist’s office to optometric screening, from a single consultation to a longitudinal patient journey supported by digital tools.

    The core logic of 2026 is a shift from reactive to proactive ophthalmology. Increasingly, the goal is to prevent disease at the stage of risk-factor modification, intervene in the earliest pathological changes, and track preclinical markers. This shift is visible across several dimensions: the growing role of telemedicine and portable diagnostics; autonomous AI becoming a public health tool; and oculomics, which enables ocular image analysis to serve as a source of early biomarkers for systemic conditions. At the same time, the treatment paradigm is evolving: where repeated procedures once dominated (for example, frequent intravitreal injections), 2026 brings a move toward extended-duration regimens, implant-based drug delivery platforms, and disease control with fewer clinic visits.

    Another important axis is the alignment of patient expectations. Some new approaches (for example, in the management of dry AMD and geographic atrophy) do not promise to “restore vision,” but rather to buy time—slowing structural retinal damage and functional vision loss. As a result, in 2026, risk–benefit communication and shared decision-making become almost as important as the choice of molecule or device itself.

    Below, we outline the key eye care trends of 2026: what is changing, why it matters, and how it will shape ophthalmic and optometric practice.

    trend pol

    1. New Approaches to Treatment

    1.1. Geographic Atrophy (GA): The Introduction of Active Treatment in eye care trends 2026

    1.1.1. Injectable Therapies as Ophthalmology Trends 2026

    Following the key trends in Ophthalmology and Optometry in 2026 , development of injectable therapies for geographic atrophy, clinical practice is entering a “second wave” phase—where the main questions are no longer whether therapy is possible for a disease historically considered untreatable, but how that therapy should be practically implemented. In 2026, the focus will be on patient selection, treatment initiation, dosing frequency and duration, as well as monitoring.

    Currently, the FDA has approved the following injectable therapies for GA:

    • Izervay (avacincaptad pegol) — a C5 complement inhibitor.
    • Syfovre (pegcetacoplan) — a C3 complement inhibitor.

    Their mechanism of action involves reducing chronic inflammation and cellular damage in the retina and—most importantly—slowing the rate of GA lesion expansion.

    Because most available data focus on slowing atrophy progression (an anatomical endpoint) rather than guaranteed improvements in visual acuity, properly managing patient expectations becomes particularly critical in 2026. Clear discussions about therapeutic goals and limitations are emphasized in review publications addressing the first approved GA treatments.

    ga injections

    1.1.2. Multiwavelength Photobiomodulation

    Multiwavelength photobiomodulation is one of the most promising emerging approaches and key trends in Ophthalmology and Optometry in 2026 aimed at halting or slowing the progression of dry AMD through modulation of mitochondrial activity. The use of specific wavelengths (red and near-infrared light, approximately 590–850 nm) may reduce oxidative stress in retinal cells, inflammation, and apoptosis of retinal pigment epithelium cells.

    Its appeal is clear: a non-invasive procedure with significantly better acceptability for some patients compared with regular injections.

    Until recently, its effectiveness remained debated, with studies showing only temporary functional improvement and reduction in drusen volume. At ARVO 2025, updated results from the LIGHTSITE III study demonstrated that photobiomodulation can significantly slow visual acuity decline and reduce the rate of GA expansion.

    In 2025, the FDA approved photobiomodulation for AMD, creating strong prospects for broader clinical adoption in 2026.

    The 2026 trend is correct positioning and stratification:

    • Use of photobiomodulation based on clear indications for specific dry AMD stages and patient profiles.
    • Transparent communication of expectations, with goals focused on functional support and slowing GA progression rather than guaranteed vision restoration.

    photobiomodulation

    1.2. Extended Anti-VEGF Treatment Regimens

    Another major trend is the shift toward regimens with reduced injection frequency. This is not merely about comfort, but primarily about preventing missed visits: patients with AMD and diabetic retinopathy with DME often fall out of treatment due to visit burden. Thus, 2026 reinforces the principle that treatment must be effective in real-world conditions, not only under ideal adherence.

    The ranibizumab port delivery system (Susvimo, Port Delivery System) has become emblematic of this trend. In 2025, the FDA also approved Susvimo for the treatment of diabetic retinopathy.

    1.3. Gene Therapy for Macular Telangiectasia Type 2 (MacTel 2)

    MacTel 2 is a chronic, progressive neurodegenerative retinal disease that previously lacked active treatment.

    In 2025, the first implantation of ENCELTO (revakinagene taroretcel)—the first and currently only FDA-approved gene therapy for MacTel 2—was performed in the United States. ENCELTO enables a shift from observation to active intervention, with the potential to preserve visual function in early-stage patients.

    The device is based on encapsulated cell therapy technology: a capsule containing genetically modified cells that continuously secrete recombinant human ciliary neurotrophic factor (CNTF), acting as a neuroprotective agent that slows photoreceptor degeneration.

    In 2026, the focus will move from “innovation storytelling” to routine clinical implementation, including defining early selection criteria, monitoring protocols (OCT biomarkers, functional testing), and accumulating real-world long-term data on photoreceptor preservation and visual function.

    1.4. Gene Therapy for Neovascular AMD: Closest to Real Transformation

    For neovascular AMD, gene therapy remains one of the most anticipated eye care trends 2026 directions, as it has the potential to fundamentally change treatment logic—from repeated injections to a single vector administration enabling long-term therapeutic protein expression. Reviews published in 2025 highlight active programs such as RGX-314, ADVM-022 (Ixo-vec), 4D-150, and others.

    In 2026, the key questions shift from “does it work?” to “how does it work across different patient groups?” including:

    • Stability and duration of expression;
    • Inflammatory and immune response profiles;
    • Need for supplemental anti-VEGF therapy;
    • Patient selection criteria;

    Injection centers and post-procedure monitoring standards.

    2. Oculomics: The Eye as a “Window to the Body” and a Source of Digital Biomarkers

    Oculomics is one of the most compelling trends of 2026, as it reshapes ophthalmology’s role within medicine as a whole. The concept is simple: the eye is the only structure where microvasculature, neurons, and signs of metabolic and inflammatory processes can be visualized non-invasively at high resolution. As a result, fundus and OCT/OCTA data may serve as biomarkers for systemic conditions—from cardiovascular risk to neurodegenerative diseases.

    oculomics

    In contemporary research, oculomics is described as an approach that uses retinal images to assess systemic risks and conditions, with potential scalability for screening. In 2026, this “scale” becomes critical: data may originate not only from ophthalmology clinics, but also from optometric practices, mobile screening programs, and telemedicine.

    What truly changes in 2026:

    • A transition from “interesting correlations” to clinical utility, with models expected to demonstrate actionable impact on patient management.
    • Data verification and management of false-positive risk, including the communication of systemic risk to patients.
    • Integration with AI, as multidimensional patterns often exceed human interpretive capacity.

    A major risk in 2026 is over-marketing, reinforcing the need for externally validated models with clear clinical context that do not generate unnecessary “medical noise.”

    3. AI Technologies: From Decision Support to Autonomous Screening and Managed Patient Pathways

    votes

    3.1. Autonomous Diabetic Retinopathy Screening as a Scalable Standard

    In 2026, diabetic retinopathy remains the most studied use case for autonomous AI. In the United States, three FDA-approved autonomous DR screening systems are already described (LumineticsCore/IDx-DR, EyeArt, AEYE-DS). This positions AI as a practical tool capable of influencing large-scale screening programs, particularly in primary care, endocrinology clinics, and mobile settings.

    The FDA approval of AEYE-DS as a fully autonomous solution (portable camera plus algorithm) underscores that in 2026, AI increasingly “works where the patient is,” not only where an ophthalmologist is present.

    3.2. 2026 as the Year of Integration

    Successful projects in 2026 will be distinguished by:

    • Image quality standards and quality control;
    • Clear referral rules and urgency levels;
    • Mechanisms to ensure patient follow-through (scheduling, reminders, visit tracking);
    • Transparent documentation for clinicians, patients, and audit purposes.

    3.3. AI as “Invisible Infrastructure”

    In 2026, AI increasingly functions as invisible infrastructure: highlighting high-risk cases, prioritizing queues, generating structured reports, and standardizing interpretation. The impact is reduced variability, faster routing, and fewer missed cases.

    4. Telemedicine: From Video Calls to Retinal Screening and Remote Management

    By 2026, telemedicine in ophthalmology is no longer synonymous with video consultations. Its foundation is tele-imaging: transmission and assessment of retinal images (fundus photos, sometimes OCT) with structured referral protocols.

    At the same time, limitations become more openly discussed. Certain conditions and components of assessment may be less accurately captured remotely, requiring clear protocols to define which patients can be managed remotely and which require in-person examination.

    The 2026 trend is a shift from “tool” to “pathway”:

    • Tele-screening as the first step;
    • Automated or semi-automated reporting;
    • Referral and follow-up control;

    Remote reassessment for ongoing risk monitoring.

    5. New Devices and Portable Diagnostics: Closer, Faster, More Scalable Care

    trend vote

    5.1. Portable Diagnostics as the Foundation of Coverage

    Portable fundus cameras and compact diagnostic systems represent one of the most practical changes of 2026. Their value lies not only in technology, but in enabling large-scale screening in locations without full ophthalmic infrastructure.

    Synergy with autonomous AI (such as AEYE-DS) is especially strong here, supporting new partnership models:

    • Endocrinology and primary care clinics;
    • Optical stores and optometric practices;
    • Mobile programs for workplaces or regions.

    5.2. Devices Deliver Value Only with Quality Protocols

    Success depends not just on acquiring devices, but on defined protocols:

    • Staff training in image acquisition;
    • Minimum quality criteria;
    • Retake rules;
    • Handling ungradable cases.

    In 2026, image quality becomes decisive, as AI and telemedicine depend on it.

    5.3. Home and Remote Monitoring for Extended Treatment Regimens as eye care trends 2026

    As treatment intervals lengthen, the risk of between-visit deterioration increases. Thus, 2026 strengthens the role of:

    • Home functional monitoring;
    • Digital questionnaires and symptom trackers;

    Remote checkpoints signaling the need for earlier recall.

    6. 2026 as the Year of Standardized Myopia Control and Greater Risk Awareness

    By 2026, myopia control is no longer debated but formalized, grounded in consensus documents and systematic reviews. Myopia is increasingly recognized as a chronic disease with stages, phenotypes, and potentially blinding complications.

    Implications for practice:

    1. Focus on preventing progression to high myopia.
    2. Combined strategies integrating behavioral, optical, and pharmacologic interventions with monitoring.
    3. A shared language between optometrists and ophthalmologists, with coordinated patient pathways.
    4. Support from AI and telemedicine for risk detection and personalized care.

    Myopia control in 2026 becomes a structured, long-term risk-reduction process.

    7. Optogenetics: Expanding the Evidence Horizon in Inherited Retinal Degenerations

    In 2026, optogenetics moves beyond concept into longer-term observation. Publications from 2025 highlight functional stabilization or improvement in retinitis pigmentosa, emphasizing pragmatic success criteria.

    For patients with severe vision loss, meaningful outcomes extend beyond visual acuity charts to spatial orientation, object recognition, and contrast sensitivity. In 2026, discussions increasingly focus on realistic endpoints and honest communication of limitations.

    8. Less Invasive Interventions and Patient Comfort as Components of Clinical Effectiveness

    Another key eye care trends 2026 is less traumatic technology that preserves efficacy while improving patient experience. A notable example is the FDA approval of Epioxa (epi-on) for keratoconus in 2025, preserving corneal epithelium and potentially reducing pain and recovery time.

    This trend spans refractive surgery, ocular surface disease, and chronic condition management, reinforcing that patient experience is integral to adherence and clinical outcomes.

    trends summary

    Conclusion

    The ophthalmology trends 2026 clearly demonstrate that ophthalmology and optometry are entering a phase of mature transformation, where success is driven not by isolated innovations but by their integration into coherent clinical pathways. The focus is shifting from treating consequences to early detection, slowing progression, and long-term management of chronic eye disease.

    Active treatment of geographic atrophy, photobiomodulation, extended anti-VEGF regimens, and the emergence of gene therapies for MacTel 2 and neovascular AMD fundamentally reshape patient management—from observation or frequent procedures to strategies aimed at preserving retinal structure and function with minimal procedural burden. These approaches require careful patient stratification and responsible expectation management, as the goal increasingly becomes slowing neurodegeneration rather than restoring vision.

    At the diagnostic level, 2026 reinforces decentralization: portable devices, telemedicine, and autonomous AI bring screening closer to patients and enable coverage of much broader populations. Oculomics and AI transform ocular images into sources of digital biomarkers that may influence not only ophthalmic but also general clinical management. At the same time, it becomes clear that technological value is defined not by algorithms or devices, but by data quality, model validation, and clearly structured patient pathways—from screening to treatment.

     

  • Diabetic Retinopathy Screening and Treatment: a Complete Guide

    dr
    AI Ophthalmology and Optometry | Altris AI Maria Znamenska
    5 min

    Diabetic retinopathy screening and treatment: a complete guide

    Table of Contents

    1. What are the diabetic retinopathy screening methods?
    2. Fundus images in DR screening
    3. Can OCT detect diabetic retinopathy?
    4. What does diabetic retinopathy look like on OCT?
    5. What is optimal diabetic retinopathy screening frequency?
    6. What is the best treatment for diabetic retinopathy?
    7. Diabetic retinopathy management: key takeaways

     

    Diabetic retinopathy (DR) remains the leading cause of irreversible vision loss among working-age adults worldwide. According to the International Diabetes Federation (IDF), one in three patients with diabetes shows signs of DR, and 10% develop diabetic macular edema (DME). Early diagnosis, systematic screening, and individualized monitoring are essential to prevent vision loss.

    What are the diabetic retinopathy screening methods?

    Modern methods of DR screening include:

    • Telemedicine platforms – enable automated transmission of fundus images
    • Mobile fundus cameras – Wi-Fi–enabled devices for field examinations
    • Smartphone-based platforms – use specialized lenses for retinal imaging
    • Optical coherence tomography (OCT) – used to detect early retinal changes and diabetic macular edema, complementing fundus photography
    • AI-based systems –  solutions for automated image analysis for fundus and OCT

    In practice, these methods are often combined. For example, patients may undergo fundus photography, after which images are sent to telemedicine centres and analysed by AI algorithms. More complex cases are then referred to ophthalmologists.

    DR screening is frequently incorporated into annual diabetes check-ups conducted by primary care physicians trained in basic fundus photography. This approach, already successfully implemented in several EU countries, has reduced the incidence of severe DR.

    Innovations in DR screening have broadened access for rural residents, older adults, and individuals with limited mobility. Integration into national e-health systems enables automated reminders and electronic medical record linkage, incorporating laboratory data (HbA1c, blood pressure) alongside retinal images.

    Fundus images in DR screening

    Fundus photography is the optimal primary screening method due to its high diagnostic yield, cost-efficiency, simplicity, and ability to integrate with AI and telemedicine solutions. 

    It enables detection of microaneurysms, hemorrhages, exudates, and neovascularization, often before symptoms arise. National screening programs rely heavily on digital fundus imaging, which, when combined with AI, provides an efficient platform for mass DR detection.

    Advances in fundus imaging for diabetic retinopathy have improved efficiency. Modern non-mydriatic cameras deliver high-quality images without pupil dilation, while automated image analysis supports rapid identification of suspicious cases. Cloud storage and telemedicine platforms facilitate remote evaluation, increasing coverage in regions with limited ophthalmology services.

    Next-generation wide-field cameras further enhance detection by capturing peripheral pathology. Some devices also generate automated annotations, reporting lesion type, DR stage, and DME presence, thereby standardizing interpretation and expediting clinical decision-making.

    Diabetic retinopathy screening with fundus
    Diabetic retinopathy detection from fundus images

    Can OCT detect diabetic retinopathy?

    Yes. OCT can detect early structural changes in the retina and is increasingly used to complement standard diabetic retinopathy screening.

    • Role in DR screening – While not a primary screening tool, OCT is now widely applied alongside fundus photography. It is especially valuable for detecting early diabetic macular edema (DME) and subtle morphological changes in the central retina not visible during ophthalmoscopy.
    • High-resolution imaging – OCT visualizes changes such as photoreceptor layer disruption, subclinical intraretinal fluid, neurosensory retinal thickening, and foveal edema. These findings often appear before clinically significant macular edema.
    • Differential diagnosis – OCT also helps identify other causes of vision loss in diabetic patients, for example, ruling out age-related macular degeneration.
    • Clinical evidence – Studies confirm that combining OCT with fundus photography increases diagnostic accuracy for DME. Experts therefore recommend this approach for patients with long-standing diabetes, poor glycemic control, or vision complaints.

    What does diabetic retinopathy look like on OCT?

    On OCT, diabetic retinopathy (DR) can appear as a combination of retinal structural damage, fluid accumulation, and microvascular changes that may not be visible on fundus photography.

    Typical OCT findings in DR include:

    • Photoreceptor damage – loss of outer retinal layers, especially the ellipsoid zone
    • Intraretinal hyperreflective foci, hard exudates
    • Microaneurysms – visible as small, round changes within the retina
    • Retinal thickness changes and neuroepithelial layer atrophy
    • Diabetic macular edema  – with intraretinal hyporeflective cystoid spaces and neuroepithelial swelling
    • Subretinal fluid  – resulting from increased vascular permeability
    • DRIL – disorganization of inner retinal layers, associated with poor prognosis
    • Epiretinal membranes – potential precursors to retinal detachment

     

    Advanced findings
    OCT can also reveal proliferative changes and tractional zones, which may progress to tractional retinal detachment.

    OCTA insights
    Beyond structural analysis, OCT angiography (OCTA) allows visualization of retinal microvascular changes without the contrast injection. OCTA helps identify areas of neovascularization, capillary network disruption, and the degree of macular ischemia.

    Diabetic retinopathy screening OCT
    Diabetic retinopathy (hyperreflective foci, moderate destruction of the ellipsoid zone and RPE), diabetic macular edema (neuroepithelium edema, intraretinal cystic cavities), epiretinal membrane

    What is optimal diabetic retinopathy screening frequency?

    The screening frequency for diabetic retinopathy is tailored to diabetes type, disease stage, and risk factors:

    Type 1 diabetes

    • First screening: 3–5 years after diagnosis (due to onset in children and young adults)
    • Then annually, if no DR is detected
    • If DR is present, frequency depends on severity

    Type 2 diabetes

    • Screening at diagnosis, as DR may already be present.
    • If no DR, repeat every 1–2 years.

    Patients with confirmed DR

    • No visible DR, mild non-proliferative diabetic retinopathy (NPDR), no DME — every 1–2 years
    • Moderate NPDR — every 6–12 months.
    • Severe NPDR — every 3 months.
    • Proliferative DR (PDR) — monthly, with regular OCT monitoring of the macula.
    • DME — monthly if center-involving, every 3 months if not.

    Pregnant women with type 1 or type 2 diabetes

    • Screening before conception or in the first trimester, with follow-up each trimester and postpartum
    • Screening is not required for gestational diabetes without pre-existing diabetes

    Post-treatment patients (laser or vitrectomy)

    • Typically, every 3–6 months during the first year, individualized based on retinal stability
    Screening DR with OCT
    Diabetic retinopathy (hyperreflective foci, microaneurysms, destruction of the ellipsoid zone and RPE), diabetic macular edema (neuroepithelial swelling, intraretinal cystic cavities), epiretinal membrane.

    Monitoring of diabetic retinopathy progression

    Ongoing diabetic retinopathy monitoring is essential to detect early signs of progression and guide treatment decisions. A key focus in monitoring is diabetic macular edema (DME), which represents fluid accumulation in the macula due to leakage from damaged retinal vessels. DME is a common complication of DR and the leading cause of vision loss in diabetic patients. OCT plays a central role in detecting DME and identifying structural changes that indicate disease progression.

    OCT biomarkers in DME

    OCT enables precise visualization of retinal layers with micron resolution, confirming DME presence and providing prognostic biomarkers for treatment selection and monitoring. 

    The main OCT biomarkers in DME include:

    • Cystoid hyporeflective intraretinal spaces – usually in the inner nuclear layer (INL) or outer plexiform layer (OPL). Their number, size, and location correlate with edema severity. Large or confluent spaces may indicate chronicity and a worse prognosis.
    • Subretinal fluid – accumulation between the neurosensory retina and retinal pigment epithelium. Often associated with a better visual prognosis, but requires close monitoring and consideration in anti-VEGF therapy.
    • Central macular thickening – a key marker of treatment effectiveness and disease activity.
    DME screening as the process of DR screening
    Diabetic retinopathy (hyperreflective foci, hard exudates), diabetic macular edema (neuroepithelial swelling, intraretinal cystic cavities).

    OCT red flags in DR progression

    Beyond DME, OCT helps identify broader signs of DR worsening that require therapy reassessment:

    • Progressive central macular thickening despite treatment
    • Increase in intraretinal or subretinal fluid, or enlargement of cystoid spaces
    • New hyperreflective foci, reflecting inflammatory activity (these may precede hard exudates or RPE changes)
    • Development or progression of disorganization of inner retinal layers (DRIL), an independent predictor of poor prognosis, even when orphological improvement is seen on OCT
    • Ellipsoid zone disruption, indicating photoreceptor damage
    • Signs of macular ischemia, although better evaluated with OCTA, indirect signs on OCT may include thinning of the inner retinal layers.
    • Tractional changes, such as epiretinal membranes, inner retinal stretching, or macular traction
    OCT biomarkers in DME
    Diabetic retinopathy (hyperreflective foci, hard exudates, destruction of the ellipsoid zone and RPE, disorganisation of the retinal inner layers (DRIL)), Diabetic macular edema (neuroepithelial swelling, intraretinal cystic cavities), subretinal fluid.

    The appearance of these OCT features should prompt clinicians to reconsider therapy, whether by switching anti-VEGF agents, introducing steroids, using combination therapy, or referring patients for surgical evaluation when traction is present.

    Example of diabetic retinopathy screening OCT
    Diabetic retinopathy (hyperreflective foci, hard exudates, destruction of the RPE), Diabetic macular edema (neuroepithelial swelling, intraretinal cystic cavities), subretinal fluid.

    What is the best treatment for diabetic retinopathy?

    The treatment of diabetic retinopathy is based on a comprehensive approach that takes into account not only the disease stage, but also individual patient characteristics, OCT findings, comorbidities, and prognostic biomarkers. Modern strategies combine preventive, pharmacological, and surgical methods, as well as personalized medicine tools based on retinal imaging.

    Criteria for treatment selection

    The choice of therapy is guided by the following parameters:

    • DR stage –  non-proliferative, proliferative, with or without DME
    • Form of macular edema –  focal, diffuse, with or without subretinal fluid
    • Presence of DRIL, EZ disruption, ischemic changes on OCTA
    • Response to previous treatment –  anti-VEGF, steroids, laser
    • Comorbidities –  renal insufficiency, hypertension, poor adherence

    For low-risk patients, observation or focal laser may be sufficient. Patients with significant DME usually require anti-VEGF or steroid injections. Those with proliferative DR often undergo panretinal laser photocoagulation or vitrectomy.

    Diabetic retinopathy treatment methods

    The main treatment options for diabetic retinopathy include pharmacotherapy, laser therapy, surgical intervention, and personalized approaches based on OCT.

    1. Pharmacotherapy: anti-VEGF and steroids

    Anti-VEGF agents such as aflibercept, ranibizumab, and bevacizumab are the first-line therapy for diabetic macular edema. They are especially effective in patients with pronounced edema and without ischemia.

    New drugs with extended duration of effect, including port delivery systems, are becoming available.

    Steroids are used when DME is persistent, when patients do not respond to anti-VEGF therapy, or in cases with an inflammatory phenotype.

    2. Laser therapy

    Injections have largely replaced laser therapy in the treatment of DME. However, panretinal photocoagulation remains the standard treatment for proliferative DR.

    Subthreshold micropulse laser is increasingly applied for focal edema, as it minimizes tissue damage.

    3. Surgical treatment

    Vitrectomy is recommended in cases of tractional macular edema, vitreous hemorrhage, or retinal detachment.

    4. Personalization with OCT

    Modern treatment protocols use OCT biomarkers to tailor therapy and improve prognosis.

    Patient education and multidisciplinary care

    DR treatment outcomes strongly depend on adherence. Patients must be informed about the need for regular injections, monitoring, and systemic control. Coordinated care involving ophthalmologists, endocrinologists, and family doctors helps maintain stable glycemic control and slows DR progression.

    Diabetic retinopathy management: key takeaways

    Diabetic retinopathy is a progressive disease, but modern diagnostics and treatments make it possible to preserve vision and improve outcomes. OCT and OCTA have become essential tools for early detection, risk assessment, and personalized therapy planning. Effective management combines pharmacotherapy, laser treatment, surgery, and patient education. Multidisciplinary care and strong patient adherence remain crucial for long-term success. With timely monitoring and tailored treatment, the progression of diabetic retinopathy can be significantly slowed.

    Disclaimer: USA FDA 510(k) Class II; Altris Image Management System (Altris IMS); AI/ML models and components intended to use for research purposes only, not for clinical diagnosis purposes.

  • Altris Achieves MDSAP Certification, Strengthening Global Presence and Clinical Credibility

    AI Ophthalmology and Optometry | Altris AI Altris Inc.
    22.08.2025
    1 min.

    22.08.2025

    Altris Achieves MDSAP Certification, Strengthening Global Presence and Clinical Credibility

    Altris Inc., a leading decision support platform for OCT scan analysis, proudly announces that it has passed the Medical Device Single Audit Program (MDSAP) audit. 

    Based on the objective evidence reviewed, this audit enables a recommendation for Initial certification to ISO 13485:2016 MDSAP, including the requirements of Australia, Brazil, Canada, the USA, and Japan, and EU 2017/745, and that the scope was reviewed and found to be appropriate for ISO 13485:2016/MDSAP and EU MDR 2017/745.

    The results of this audit are suitable for obtaining the EU MDR 2017/745 certificate, which we are currently in the process of pursuing.

    ISO 13485:2016/MDSAP enables Altris Inc. to “design, manufacture, and distribute medical software for the analysis and diagnosis of retinal conditions globally.” It is recognized by leading global health regulators and signals trust and credibility to public and private hospitals, eye care networks, and optometry chains worldwide. 

    MDSAP Certification also opens the door for Altris Inc. to enter new international markets, including Asia-Pacific, Latin America, and additional parts of North America. The MDSAP certification allows a single regulatory audit of Altris AI’s Quality Management System (QMS) to be recognized by multiple major health authorities, including:

    • FDA (United States)
    • Health Canada
    • TGA (Australia)
    • ANVISA (Brazil)
    • MHLW/PMDA (Japan)

    MDSAP enforces that the Quality Management System for developing, testing, and maintaining AI Decision Support for OCT complies with international medical device standards. Altris AI Decision Support for OCT Analysis system that facilitates the detection and monitoring of over 70 retinal pathologies and biomarkers, including early signs of glaucoma, diabetic retinopathy, and age-related macular degeneration. 

    “Achieving ISO 13485:2016 certification under the stringent MDSAP requirements is a significant accomplishment for our team,” said Maria Znamenska, MD, PhD, Chief Medical Officer at Altris AI. “As a practicing ophthalmologist, I understand that the safety of patients is the absolute priority. Especially when implementing such an innovative technology as AI for decision support in OCT analysis. That is why we did everything possible to build quality processes that guarantee the highest level of safety for the patients.

    This certification enables Altris AI to expand its presence and offer eye care specialists upgraded functions such as GA progression monitoring, flags for smart patient filtering, or automated drusen count.”

    “This is more than a regulatory milestone for our team  – it’s a signal to the global eye care community that Altris AI is a trusted clinical partner,” said Andrey Kuropyatnyk, CEO of Altris AI. 

    About Altris 

    Founded in 2017, Altris AI is at the forefront of integrating artificial intelligence analysis into ophthalmology and optometry.

    The company’s platform is designed to assist eye care professionals in interpreting OCT scans with greater objectivity and make informed treatment decisions. It’s a vendor-neutral platform compatible with OCT devices from 8 major global manufacturers. With a commitment to innovation and compliance, Altris AI continues to develop solutions that set higher standards in the eye care industry and improve patient outcomes.

    Disclaimer: USA FDA 510(k) Class II; Altris Image Management System (Altris IMS); AI/ML models and components intended to use for research purposes only, not for clinical diagnosis purposes.

     

  • Glaucoma OCT Monitoring Guide: From Detection to Long-Term Care

    glaucoma
    AI Ophthalmology and Optometry | Altris AI Maria Znamenska
    5 min

    Glaucoma OCT Monitoring Guide: From Detection to Long-Term Care

    Table of Contents

    1. Glaucoma detection: why early diagnosis is critical
    2. How to detect glaucoma in early stages: key approaches
    3. Advanced imaging for glaucoma: OCTA
    4. OCT glaucoma monitoring after diagnosis
    5. Additional tools for monitoring glaucoma treatment
    6. Glaucoma OCT: the foundation of long-term glaucoma care

    Optical Coherence Tomography (OCT) has fundamentally changed glaucoma diagnostics over the past two decades. It enables non-invasive, micron-level imaging of retinal microstructures and provides objective measurements of the retinal nerve fibre layer (RNFL), ganglion cell complex (GCC), and optic nerve head (ONH) parameters. Moreover, the advent of OCT angiography (OCTA) has introduced a new dimension in assessing microcirculation—complementing structural analysis and potentially predicting glaucoma progression.

    Today,  OCT is the standard for early detection, monitoring, and risk stratification of glaucoma progression, as recognised in international clinical guidelines. When combined with functional tests, tonometry, and anterior chamber angle assessment, OCT becomes the foundation for personalised glaucoma management.

    Glaucoma detection: why early diagnosis is critical

    Early glaucoma diagnosis is vital, as optic nerve damage caused by the disease is irreversible. Many patients seek care only after significant vision loss has occurred, at which point treatment may slow progression but cannot restore lost function. This is why ophthalmologists emphasise the importance of glaucoma detection at preclinical or pre-perimetric stages.

    How does OCT help in early glaucoma detection?

    OCT provides high-resolution imaging of the retina and optic nerve head. Unlike subjective functional tests, OCT delivers objective, quantitative data on ganglion cells, nerve fibre layers, and the neuroretinal rim, enabling recognition of even subtle structural changes.

    Recent OCT models go further, allowing detailed visualisation of the lamina cribrosa, a structure known to be altered in glaucoma. Today, OCT is recognised as a key diagnostic tool in the guidelines of both the European Glaucoma Society and the American Academy of Ophthalmology.

    How to detect glaucoma in early stages: key approaches

    Early glaucoma detection relies on evaluating structural and functional parameters of the eye, supported by advanced imaging techniques. The three main parameters assessed with glaucoma OCT are:

    • Ganglion Cell Complex (GCC) thickness and asymmetry
    • Retinal Nerve Fibre Layer (RNFL) thickness
    • Optic nerve head parameters with the DDLS scale

    In addition, OCT Angiography (OCTA) provides complementary insights into ocular microvasculature that may indicate early glaucomatous damage.

    Glaucoma detection parameter 1: GCC thickness and asymmetry

    One of the most sensitive preclinical biomarkers of glaucomatous damage is thinning of the ganglion cell complex (GCC), which includes the ganglion cell layer (GCL), inner plexiform layer (IPL), and macular RNFL (mRNFL). It is assessed through macular OCT scans. Damage in this area is particularly critical, as 50–60% of all ganglion cells are concentrated within the central 6 mm zone.

    Assessing asymmetry between the superior and inferior halves of the macula within the GCC is a key diagnostic indicator. Studies show that minimum GCC thickness and FLV/GLV indices (Focal Loss Volume / Global Loss Volume) are predictors of future RNFL thinning or emerging visual field defects. Asymmetry maps significantly ease clinical interpretation.

    A newer approach—vector analysis of GCC loss—also allows clinicians to visualise the direction of damage, which often correlates with future visual field defects.

    Measuring Ganglion Cell Complex (GCC) Thickness and GCC Asymmetry

    Glaucoma detection parameter 2: RNFL thickness analysis

    RNFL analysis is among the most widely used glaucoma diagnostic methods. The RNFL reflects the axons of the ganglion cells and is readily measured in optic nerve scans. Temporal sectors are the most sensitive and often show the earliest changes.

    Even when the overall thickness appears normal, localised defects should raise suspicion. Sectoral thinning of ≥5–7 μm is considered statistically significant. Age-related RNFL decline (~0.2–0.5 μm/year) must also be considered.

    Glaucoma detection parameter 3: optic nerve head parameters and the DDLS scale

    Evaluating the optic nerve head (ONH) is essential. OCT enables automated assessment of optic disc area, cup-to-disc ratio (C/D), cup volume, rim area, and the lamina cribrosa.

    The Disc Damage Likelihood Scale (DDLS) classifies glaucomatous ONH changes based on the thinnest radial rim width or, if absent, the extent of rim loss. Unlike the C/D ratio, DDLS adjusts for disc size. When combined with OCT, DDLS significantly enhances objective clinical assessment.

    In high myopia, automatic ONH segmentation often misclassifies anatomy. Here, newer deep learning–based segmentation models improve accuracy.

    Evaluating the optic nerve head (ONH)

    Advanced imaging for glaucoma: OCTA

    OCT Angiography (OCTA), an advanced glaucoma OCT technique, provides unique insights into ocular circulation. It enables evaluation of:

    • Vessel density in the peripapillary region
    • Optic nerve and macular vascularisation
    • Retinal versus ONH perfusion in both eyes

    OCTA for early glaucoma detection

    Studies confirm that reduced vessel density correlates with RNFL loss and visual field deterioration, and often precedes both.

    OCT glaucoma monitoring after diagnosis

    Glaucoma can progress even with stable intraocular pressure (IOP), making regular structural assessment of the optic nerve and inner retina crucial for therapy adjustment.

    Glaucoma OCT is not only a diagnostic tool but also the primary method for monitoring glaucomatous damage. Unlike functional tests, OCT can detect even minimal RNFL or GCL thinning months or even years before visual field loss appears. With serial measurements and built-in analytics, OCT allows clinicians to track glaucoma progression rates and identify high-risk patients.

    Methods for glaucoma progression monitoring

    There are two main approaches to monitoring glaucoma progression with OCT:

    Method 1: event-based analysis

    This method compares current scans with a reference baseline, identifying whether RNFL or GCL thinning exceeds expected variability.

    ? Example: Heidelberg Eye Explorer (HEYEX) highlights suspicious areas in yellow (possible loss) or red (confirmed loss).

    Limitations include sensitivity to artifacts, image misalignment, and segmentation quality. A high-quality baseline scan is essential.

    Method 2: trend-based analysis

    This approach accounts for time. The software plots RNFL/GCL thickness trends over time in selected sectors or globally and calculates the rate of progression.

    Examples:

    • RNFL thinning >1.0 μm/year is clinically significant.
    • Thinning >1.5 μm/year indicates active progression.

    It also accounts for age-related changes, helping differentiate physiological vs. pathological decline.

    Visual assessment in glaucoma OCT

    Qualitative analysis also plays an important role in detecting glaucoma progression. Key aspects include:

    • Focal RNFL thinning (localised defects)
    • Changes in the neuroretinal rim
    • Alterations in ONH cupping
    • GCL/GCIPL comparison (superior vs. inferior) on macular maps
    • New segmentation artifacts (may mimic progression)

    Visual glaucoma OCT analysis

    OCT glaucoma findings that indicate true progression

    Five OCT findings suggest true glaucomatous progression:

    1. RNFL thinning >10 μm in one sector or >5 μm in several sectors
    2. New or worsening GCL asymmetry (yellow to red colour shift)
    3. Emerging or expanding RNFL defects on colour maps
    4. Increasing C/D ratio with concurrent rim thinning
    5. New localised areas of vessel density loss on OCTA

    Particular attention should be paid to the inferotemporal and superotemporal RNFL sectors, where 80% of early changes occur.

    Frequency of glaucoma OCT monitoring

    According to the AAO and EGS, the recommended frequency for OCT glaucoma monitoring is:

    • High-risk patients: every 6 months
    • Stable patients: once a year
    • For trend analysis: at least 6–8 scans over 2 years to ensure statistical reliability

    Looking ahead, broader use of AI for glaucoma is expected to support earlier and more accurate detection, while also reducing false positives.

    Additional tools for monitoring glaucoma treatment

    While glaucoma OCT is essential for detecting structural changes, a comprehensive glaucoma assessment requires a multimodal approach. Additional tools include perimetry, tonometry, optic disc fundus photography, and gonioscopy.

    Perimetry (visual field testing)

    Functional assessment of the optic nerve remains crucial. Standard Automated Perimetry (SAP), most often performed with Humphrey Visual Field Analyzer protocols (24-2, 30-2, 10-2), is the most widely used method.

    Key indices:

    • MD (mean deviation): average deviation from normal values
    • PSD (pattern standard deviation): highlights localised defects
    • VFI (visual field index): summarises global visual function; useful for tracking glaucoma progression
    • GHT (glaucoma hemifield test): automated analysis of field asymmetry

    ? Important: In 30–50% of cases, structural changes such as RNFL thinning on OCT precede visual field defects; in others, functional loss appears first. Best practice relies on integrated OCT and perimetry to correlate damage location and monitor glaucoma progression more precisely.

    Combined OCT and perimetry remains the gold standard for progression monitoring.

    Tonometry

    Intraocular pressure (IOP) is the only clearly modifiable risk factor associated with both glaucoma onset and progression.

    • Goldmann applanation tonometry remains the gold standard.
    • A single IOP reading is insufficient — diurnal fluctuations are an independent risk factor, particularly in normal-tension glaucoma.

    Optic disc fundus photography

    Although subjective, fundus imaging remains valuable for documenting glaucomatous changes, especially in borderline cases. Unlike OCT, it does not provide quantitative data but helps visualise morphology over time.

    What to assess:

    • Progressive disc cupping
    • Changes in neuroretinal rim shape or colour
    • Disc margin haemorrhages (linked to faster RNFL thinning and visual field loss)
    • Inter-eye comparisons

    Gonioscopy

    Gonioscopy evaluates the anterior chamber angle and helps exclude angle-closure, pigmentary, or pseudoexfoliative glaucoma. It also identifies:

    • Neovascularisation
    • Trabecular meshwork abnormalities
    • Other angle anomalies

    Patient education: a key to successful glaucoma management

    Accurate glaucoma detection and therapy are not enough; adherence to monitoring and treatment is equally critical.

    The challenge:

    • Early-stage glaucoma is asymptomatic.
    • Many patients underestimate its seriousness, leading to poor compliance, missed follow-ups, and discontinuation of therapy.

    The goals of patient education:

    • Explain that glaucoma progresses silently but can lead to irreversible blindness if untreated.
    • Use real-life examples (before/after OCT scans, visual field comparisons) to illustrate progression.
    • Teach patients to recognise warning signs (vision changes, eye pain).
    • Visualise disease progression with AI tools showing RNFL loss and future risk.

    Educational resources may include:

    • Printed brochures in patient-friendly language
    • Videos featuring OCT images with explanations
    • Doctor–patient in-clinic discussions
    • Telemedicine platforms with reminders and follow-up prompts

    According to the AAO, patients who understand glaucoma are 2.5 times more likely to adhere to treatment and attend check-ups.

    Glaucoma OCT: the foundation of long-term glaucoma care

    Glaucoma OCT now plays a central role in both diagnosis and monitoring. Its ability to detect subtle structural changes before measurable functional loss makes early intervention possible and increases the chances of preserving vision.

    But technology alone is not enough. Accurate interpretation, combined with strong patient education, is essential. When patients understand their disease and the role of glaucoma OCT in treatment, adherence improves and outcomes are better.

    OCT is not just a diagnostic device; it is the cornerstone of an integrated glaucoma management strategy, from initial screening to long-term monitoring and treatment optimisation.

    Disclaimer: USA FDA 510(k) Class II; Altris Image Management System (Altris IMS); AI/ML models and components intended to use for research purposes only, not for clinical diagnosis purposes.

Recently Posted

  • Business case: AI as a second opinion for OCT scans

    Altris AI for Buckingham and Hickson Optometry, the UK

    AI Ophthalmology and Optometry | Altris AI Altris Inc.
    1 min.

    Business case: Altris AI for Buckingham and Hickson Optometrists

    The Client: Buckingham and Hickson is a family-run optometry practice that was established in 1960 in the United Kingdom. The optometry practice offers a number of services:

    • Wide range of spectacle frames and lenses.
    • Contact lenses.
    • Glaucoma referral refinement.
    • Cataract choice referral.
    • OCT examination.
    • NHS and private eye tests.

    The challenge: The optometry owners wanted to test how Artificial Intelligence can assist them in OCT examination or, to be more precise, in providing a second opinion for OCT scans.

    OCT examination is one of the best retina diagnostics methods, however in many cases OCT scan interpretation can be really challenging for several reasons:

    1. Variability in Anatomy: There is significant natural anatomical variation among individuals. What may be considered normal for one person may be abnormal for another. Eye care specialists need to account for these variations when interpreting OCT scans, but this often requires years of experience.
    2. Various Eye Conditions: Eye care specialists use OCT scans to diagnose and monitor a wide range of eye conditions, including macular degeneration, diabetic retinopathy, and retinal detachment, among others. Each of these conditions can manifest in different ways on OCT scans, making interpretation challenging.
    3. Progression Monitoring: Ophthalmologists often use OCT to monitor disease progression and the effectiveness of treatment. Tracking subtle changes over time can be difficult, as it requires precise comparisons of multiple scans.
    4. Artifacts: OCT scans are susceptible to artifacts, such as shadowing, motion artifacts, and signal dropout, which can obscure or distort the image. Recognizing and mitigating these artifacts is essential for accurate interpretation.
    5. Experience and Training: Accurate interpretation of OCT scans in optometry and ophthalmology requires specialized training and experience.
    6. Evolving Technology: OCT technology continues to advance, introducing new techniques and capabilities. Staying current with these advancements and understanding their clinical implications is an ongoing challenge for ophthalmologists.

    The solution: Artificial intelligence (AI) can play a significant role in OCT (Optical Coherence Tomography) scan interpretation for ophthalmologists and optometrists in various ways. Artificial Intelligence (AI) provides eye care specialists with more accurate results, severity level detection ( to work only with pathological scans), and assists in early pathologies detection.
    According Ian, one of the owners of Buckingham and Hickson optometry, “they are using Altris AI to get a second opinion on OCT scans.”
    According to Altris AI Medical Director, Maria Znamenska, who is MD, Ph.D., Associate Professor of Ophthalmology, “It is getting more common to double-check the interpretation of OCT scans ( and other medical images) with modern AI tools as they are getting safer and more efficient. Altris AI has received FDA clearance recently apart from having a CE certificate.”

    Disclaimer: USA FDA 510(k) Class II; Altris Image Management System (Altris IMS); AI/ML models and components intended to use for research purposes only, not for clinical diagnosis purposes.

  • AI for OCT analysis in optometry chains: 8 Reasons to invest

    AI Ophthalmology and Optometry | Altris AI Mark Braddon
    5 min.

    AI for OCT analysis in optometry chains

    Optometry chains offer a wide range of eye care services, making it convenient for patients to access eye care locally. 

    However, the widespread accessibility of optometry chains has a reverse side for them. The shortage of employees, new unfamiliar equipment for diagnostics, and a large number of patients create an extremely challenging workflow for many optometrists. This, in turn, creates a number of challenges that can be more familiar to Optometry chains: low optometrist recruitment and retention, inconsistent quality of examination throughout the practices, lack of communication with patients, etc. 

    Automation of routine processes and digitalization have always served as answers to challenges like these in any industry, and healthcare is no exception. Luckily, automation of one of the most complex tasks for optometrists – OCT examination is already available to optometry chains with Artificial Intelligence (AI).   

    OCT proves to be one of the most efficient diagnostic tools for many modern top-notch optometry practices, however, mastering it requires skills and time. Artificial intelligence tools, such as AI for OCT analysis platform, can automate many routine processes which will have enormous benefits for any optometry chain. The top 8 benefits are the following: 

    • #1 AI for OCT increases clinical efficiencies

    Automating OCT scan analysis through AI reduces the time optometrists spend on image interpretation. This allows optometrists to focus on more complex cases, patient interactions, and personalized treatment plans. For any large optometry chain, saving time means providing more patients with high-quality service. 

    How does it work in practice?

    For instance, Altris AI has a severity grading of b-scans. Severity grading means that it is easy to see if the eye is healthy ​(removing any need to spend time interpreting) or highlight ​where the pathology is and the degree of severity. ​

    • Green- no pathology detected
    • Yellow- mild to medium level of severity
    • Red – severe pathology detected

    • #2 AI for OCT provides consistently high standard of quality throughout the chain

    AI algorithms provide consistent and standardized analysis regardless of the individual interpreting OCT scans. This reduces variability in diagnoses and ensures that patients receive uniform care across different clinics and practitioners within the optometry chain.

    AI algorithms can analyze OCT scans with incredible precision and consistency. They can detect subtle changes in retinal structures that might be missed by human observers, leading to earlier and more accurate diagnoses of various eye conditions such as macular degeneration, glaucoma, diabetic retinopathy, and more.

    This will help younger less experienced optometrists and will serve as a second opinion tool for more experienced specialists. 

    • #3  AI for OCT enables better retention of employees

    The shortage of optometrists in the world is staggering. 14 million optometry specialists are needed worldwide according to the WHO, while today there are only 331K ready to work.

     It is equally difficult to hire and retain a good optometrist for a company in 2023. However, more and more young optometrists choose innovative businesses that use technology to improve the workflow. Top-notch equipment, convenient scheduling tools, and of course, Artificial Intelligence for OCT & fundus photo analysis might be the perks that will help optometrists to choose your optometry business. 

    Fresh from college optometrists feel more confident when they know that they will have a backup when reviewing OCT scans

    • #4 Reduced Workload Burden

    Optometrists often have heavy workloads, and AI can help alleviate some of this burden by handling routine tasks like initial image analysis. This enables optometrists to spend more time on patient consultations and treatment planning.

    According to a survey by the General Optical Council, 57% of optometrists worked beyond their hours in 2022. Optometrists were more likely to be working beyond their hours (60%) or finding it difficult to provide patients with the sufficient level of care they needed (34%) when compared to other registration types.

    It is possible to outsource preliminary image analysis to Artificial Intelligence tools but communication and empathy are human tasks only. 

    • # 5 AI promotes enhanced patient education

    Let’s not forget about the patients. AI-generated OCT reports can help explain complex medical conditions to patients in a more understandable, visual way. After all 80% of all the information we receive is visual: imagine your optometrists not only telling but also showing what is going on with patients.  

    Comprehensive, color-coded OCT reports may improve patient education and engagement, leading to better treatment adherence and loyalty. 

    When patients don’t understand what they are paying for they are not likely to return for annual checkups. At Altris AI we created smart OCT reports that are comprehensible for patients as well as optometrists. We visualize all the pathologies and the patients can trace the dynamics of 

    #6 Reducing a clinical risk. No chances of getting a legal inquiry because of a pathology missed

    Optometry chains can perform around 40K OCT scans a week. Statistically speaking, the chance of missing a minor early pathology is huge simply because of the big number.

    With the double-check that AI for OCT scan analysis provides, It is not possible to wipe the risk out for 100%, but it is possible to diminish the risk to the absolute minimum. 

    For the optometry chain, it might mean no bad PR and weird stories in the papers and subsequently, a better brand image.

    • #7 AI makes early detection of pathologies possible on OCT

    AI algorithms can identify early signs of eye diseases that might not be easily recognizable in their early stage. This early detection can lead to timely interventions, preventing or minimizing patient vision loss.

    Glaucoma, Wet AMD, Diabetic Retinopathy, and genetic diseases are among the pathologies that lead to blindness if not detected in time. Detecting pathological signs and pathologies related to these disorders in time can literally save patients from future blindness.

    Early detection of pathologies means that it is possible to stop or reduce the risk of total blindness which is the best result in any sense. Early detection will allow optometrists to give valid recommendations, and advise on dieting and supplements right at the optical store. 

    • #8 Competitive Edge

    AI is a buzzword, and it’s not accidental. All major players understand its enormous value and invest in it. During the last presentation, the CEO of Google said “AI” 140 times, and let’s be honest, it is not to show off. It is because AI can actually make changes in business: automation of repetitive processes, workflow optimization, and human error reduction. 

    Adopting AI technology for OCT analysis showcases the optometry chain’s commitment to staying at the forefront of technological advancements in healthcare. Gaining a real competitive edge is another big goal. 

    This can attract patients who value cutting-edge approaches to diagnosis and treatment. A younger generation of patients are curious about new technologies, and this can be an additional lead magnet for them.

    Conclusion

    Incorporating AI for OCT analysis into optometry chains can enhance patient outcomes, make the workflow more efficient, and improve the performance of each optometry center. However, it’s important to ensure that the AI systems are properly validated, integrated into clinical workflows, and monitored to maintain their accuracy and effectiveness. More than that, it should complement, not replace, the expertise of optometrists. The technology should be used as a tool to aid optometrists and make OCT examination more effective.

     

    Disclaimer: USA FDA 510(k) Class II; Altris Image Management System (Altris IMS); AI/ML models and components intended to use for research purposes only, not for clinical diagnosis purposes.

  • Normative database OCT

    Normative Database in OCT: Limitations and AI Solutions

    AI Ophthalmology and Optometry | Altris AI Maria Martynova
    06.09.2023
    6 min read

    Normative Database in OCT: Limitations and AI Solutions

    The first normative database for OCT was created in the early 2000s and were based on small studies of mostly white patients. However, as OCT technology has evolved, so too have the normative databases. Recent databases are larger and more diverse, reflecting the increasing ethnic and racial diversity of the population.

    Nowadays, eye care specialists use normative database to compare the characteristics of a patient to a population-wide norm. This allows them to quickly and easily assess whether a patient’s retinal dimensions fall within normal limits. According to our survey, 79% of eye care specialists rely on the normative databases for OCT verdict with every patient.

    Normative database OCT

    However, despite the fact that normative databases are very widespread among specialists worldwide, they are not perfect. They can be affected by factors such as age, gender, axial length, and refractive error.

    They can be influenced by low image quality due to different eye pathologies. It is essential to be aware of these limitations when interpreting normative data OCT parameters. That is why, in this article, we will discuss the benefits of the collaboration between AI decision-making tools and normative databases to improve patient outcomes.

    What is a normative database for OCT

    Before diving into the subject of the benefits and limitations of normative databases, we would like to remind you what a normative database is. From the moment of its invention, the OCT exam has rapidly gained widespread adoption and has become indispensable in the eye care practice. Critical to this success has been the ability of software to automatically produce important measurements, such as the thickness of the peripapillary retinal nerve fiber layer (RNFL) in tracking glaucoma progression or the total retinal thickness in the assessment of macular diseases. 

    In order to accurately interpret OCT scans, normative databases were created. These databases are now built into almost all commercial OCT devices, allowing eye care specialists to view colored reports and progression maps that assist in the rapid recognition and tracking of pathology.

    Summing up, a normative database for OCT is a set of data that provides references for OCT thickness measurements in a healthy population. These databases are used to compare the OCT measurements of your patient to a population-wide norm. 

    Here are some of the OCT parameters that are commonly measured and compared to normative databases:

    • Retinal nerve fiber layer (RNFL) thickness: the RNFL is a retinal layer that is measured around the optic nerve. This measurement is important for diagnosing optic nerve atrophy.
    • Macular thickness: the macula is responsible for sharp central vision.
    • Ganglion cell complex thickness: the ganglion cell complex is a group of cells in the retina that are responsible for transmitting visual information to the brain.
    • Cup-to-disc ratio, neuroretinal rim, and other optic nerve parameters: are very important for diagnosing glaucoma and other optic nerve pathologies

    These are just a few of the OCT parameters that are commonly measured in normative databases. The specific parameters that are measured can vary depending on the type of OCT device and the clinical application. 

    In addition, different OCT devices can have different measurement capabilities and resolutions. For example, a device that uses time-domain OCT (TD-OCT) technology may have a lower resolution than a device that uses spectral-domain or swept-source OCT (SD or SS-OCT) technology. This means that the normative database for a TD-OCT device may not be as accurate as the normative database for an SD or SS-OCT device.

    What is more, the normative database for a particular device may be based on a specific population of patients. What are the benefits and limitations of normative databases?

    Now that we have highlighted different aspects of the normative database definition let us discuss the benefits and limitations of this tool. Normative databases can sometimes be very helpful for eye care specialists in diagnosis, decision-making, and creating a treatment strategy for eye diseases such as glaucoma and macular degeneration.

    • The measurement provided by the normative database can be used as a baseline for tracking a patient’s response to medication or other treatment. Eye care specialists can track changes between a few visits and determine the impact on the patient.
    • Normative databases show deviations from the norm, which may be a reason for a more comprehensive examination.
    • Eye care specialists can also use normative databases to compare the results of different OCT devices. This can help to ensure that they are using the most accurate device for their patients.

    There are still challenges that must be overcome to develop normative databases sufficient for use in clinical trials. That is why current normative databases also have a lot of limitations.

    Does not detect pathology

    The normative database works only with the thickness of the retina and does not detect what is inside the retina. Therefore, it cannot detect all pathologies where there is no change in retinal thickness. In the early stages, these are absolutely all diseases. We can see deviations from the normative base only when the disease progresses to a later and more severe stage when the retinal thickness decreases or increases.

    Limited diversity

    Normative databases can be limited by factors like age, gender, and ethnicity of the population used to create them. This can result in reduced accuracy for patients who are not well-represented in the database.

    Population variation

    Even healthy patients can have some anatomical variations that fall within the range of normal. These variations may be falsely flagged as abnormalities when compared to the database.

    How Altris AI platform can complement the information provided by the normative database

    Normative databases in OCT play a crucial role in aiding diagnosis and treatment planning, but they also have limitations related to representation, disease progression, and data quality. Eye care specialists need to interpret the results in the context of the patient’s individual characteristics and other clinical information, using additional tools for scan interpretations.

    Sometimes, low-quality OCT scans can be inaccurately interpreted by the eye care specialist, and the normative database can showcase inaccurate measurements. Altris AI platform detects low-quality scans automatically and warns about the possibility of inaccurate results. In addition, the platform automates the detection of 70+ pathologies and pathological signs. Once the user uploads the scan, they can see visualized and highlighted pathological areas and pathology classification that the algorithm has detected. The user can also calculate the area and volume of detected biomarkers.

    Normative database OCT

    Artificial intelligence-based tools for OCT interpretation used along with normative databases can play a crucial role in clinical eye care. Altris AI, for example, can provide eye care specialists with additional and more precise information about separate retinal layer thickness. The system analyzes the thickness of each retina layer or several layers combined.

    Normative database OCT

    While normative databases provide information only about the thickness, AI tools equipped with deep learning models can detect pathological signs in OCT scans that might be missed by the normative database or the human eye, enhancing diagnostic accuracy. Altris AI algorithm classifies the OCT scans based on the degree of pathology found. It can distinguish green concern, which indicates normal retina, yellow – moderate with slight deviations, and red concern, which means high severity level.

    Normative database OCT

    Summing up

    Despite their limitations, normative databases are an essential tool for the clinical use of OCT. They provide a valuable reference point for assessing patients and can help to identify some diseases. However, the normative database measures only the thickness, which is not enough to accurately diagnose the patient and create a treatment plan.

    That is why incorporating AI into OCT interpretation streamlines the decision-making process. By automating the initial analysis of OCT scans, specialists can focus their attention on more complex cases, making the best use of their skills and experience. Moreover, embracing AI technologies empowers eye care specialists to personalize patient care with greater precision.

    Disclaimer: USA FDA 510(k) Class II; Altris Image Management System (Altris IMS); AI/ML models and components intended to use for research purposes only, not for clinical diagnosis purposes.

  • AI blindness prevention

    AI Blindness Prevention: how AI can combat vision loss?

    AI Ophthalmology and Optometry | Altris AI Maria Martynova
    07.08.2023
    9 min read

    AI for Eye Diseases: how AI can combat vision loss?

    The total number of people with near or distant vision impairment reaches 2.2 billion worldwide.

    Of these, 43 million people are blind, and 295 million are suffering from moderate to severe visual impairment. Although the numbers are constantly changing as new research is conducted, the global burden of blindness and visual impairment remains a significant problem of humanity in the fight against which specialists combine their forces with AI technologies.

    AI blindness prevention

    AI blindness prevention tools are being actively developed to transform the landscape of vision care in many ways. Eye care specialists use AI systems for screening and detecting diseases that lead to vision loss. AI-powered smart monitors assist specialists in finding proper contact lenses and glasses. In addition, many researches are held with the help of AI algorithms, as they are able to process vast amounts of data.

    In this article, we will discuss different applications of AI in blindness prevention, specifically how artificial intelligence tools can empower eye care specialists and extend beyond the clinical setting. 

    How to Prevent Blindness: Conditions and Risk Factors

    Before talking about the developments in the AI sector toward blindness prevention, we would like to discuss the most common causes and risk factors of this impairment. Many health and lifestyle factors can influence the risk of vision loss. Smoking, excessive alcohol consumption, sun exposure, and poor nutrition can contribute to diseases that lead to vision loss. 

    In addition, there are many conditions that can lead to blindness if left with no proper treatment, among which are the following. 

    Age-related eye diseases

    The global population is aging rapidly. The number of people aged 65 and over is projected to triple from 1 billion in 2020 to 2.1 billion in 2050. Considering this fact, age-related eye diseases have become a prominent cause of blindness. Such diseases as age-related macular degeneration (AMD), cataract, and glaucoma are more prevalent in older patients, and if left untreated, they can lead to fast and significant vision loss. Regular eye check-ups and timely interventions are crucial in managing these diseases and preventing severe visual impairment.

    AI blindness prevention

    Besides AMD, there are a lot of age-related conditions which can be a red flag when examining the patient. Among these are macular holes, mactel, and vascular diseases, for example,  central retinal vein occlusion (CRVO) and central retinal artery occlusion (CRAO). Detecting even one of these pathological conditions in the early stages of their development is crucial for preventing vision loss. 

    However, many eye care specialists sometimes don’t have enough resources to dedicate more time to analyzing patients’ images. Our recent survey detected that among more than 300 participating optometrists, 40% of them have more than 10 OCT exams per day. Meanwhile, 35% of eye care specialists have 5-10 OCT examinations per day. The greater the number of patients per day, the greater the likelihood that eye care specialists may miss some minor, rare, or early conditions.

    AI blindness prevention

    Fortunately, nowadays, there are a lot of ways to empower the clinical workflow, and AI blindness prevention tools are gaining popularity. Artificial intelligence systems like Altris AI can analyze retinal images and other diagnostic data to detect early signs of age-related eye diseases. Altris AI platform, for example, can detect 70+ pathologies and pathological signs, including the ones, that refer to age-related diseases.

    AI blindness prevention

    Altris AI platform allows eye care specialists to rely on its disease classification when diagnosing a patient. It detects all the most common age-related pathologies, such as AMD, mactel, and vascular diseases – CRVO, CRAO.

    AI blindness prevention

    Diabetes and diabetic retinopathy

    Diabetes and related conditions are also common causes of vision loss. In the United States, about 12% of all new cases of blindness are caused due to diabetes. Globally, diabetes is estimated to cause 4.8% of all blindness. In addition, the risk of blindness from diabetes increases with the duration of diabetes. People with untreated diabetes for years are 25 times more likely to be blind than people without diabetes.

    AI blindness prevention

    The complication of diabetes, called Diabetic retinopathy (DR), affects the blood vessels of the retina and can lead to impaired vision or blindness. With the rising prevalence of diabetes worldwide, DR has become a significant problem. Early detection, proper control of diabetes, and regular eye exams are essential to prevent vision loss. 

    The American diabetes association (ADA) recommends that people with diabetes have an OCT scan of their eyes every year. This is because OCT can help to detect early signs of DR with high precision. In some cases, eye care specialists may recommend more frequent OCT scans. This may be the case if the patient has advanced diabetic retinopathy or a family history of diabetic retinopathy.

    AI blindness prevention

    AI algorithms such as Altris AI can assist in detecting the pathological signs of diabetic retinopathy or diabetic macular edema. Our web platform differentiates certain pathological signs that indicate diabetes-related diseases. Among these are:

    • Intraretinal fluid
    • Subretinal fluid
    • Hard exudates
    • Hyperreflective foci
    • Epiretinal fibrosis

    Genetic and inherited conditions: AI for visually impaired

    Some patients are at a greater risk of developing visual impairment due to genetic factors or the inheritance of certain conditions. For example, retinitis pigmentosa is an inherited disease that affects the photoreceptor cells in the retina and gradually leads to night blindness and loss of peripheral vision. Genetic testing and counseling can help identify people at risk and provide early intervention.

    AI blindness prevention

    Some genetic eye conditions, such as myopia, vitelliform dystrophy, or retinoschisis, can be detected in the early stages with the help of OCT examination and artificial intelligence systems. Altris AI platform can help eye care specialists in their daily practice and make eye care more accessible, allowing specialists to perform regular eye check-ups, and provide timely treatment of genetic conditions.

    AI blindness prevention

    Current ways to prevent blindness with AI 

    As you can see, blindness risk factors encompass a wide range of conditions, pathologies, and circumstances that can significantly impact a patient’s health and increase the likelihood of severe visual impairment. Poorly managed age-related eye diseases, genetic and hereditary factors, and chronic health conditions can lead to eye-related complications, further elevating the risk of blindness.

    AI blindness prevention

    In the following paragraphs, we will describe in detail the modern ways of using artificial intelligence to detect and prevent blindness: from AI-based retinal imaging for early detection of eye diseases to personalized treatment recommendations and remote patient monitoring.

    AI for image interpretation

    AI blindness prevention

    It is important to understand that the timely detection of eye diseases is key to the effective treatment of visual impairments. However, today we have an unfortunate tendency to diagnose severe forms of disease too late. A large-scale survey by Eyewire conducted in 2021 found that about 40% of people in the USA said they had not had an eye exam in more than a year, and 10% said they had not had one in more than five years. 

    In addition, recent research by the British Journal of Ophthalmology found that 25.3% of people in Europe over the age of 60 have early signs of AMD. In the UK, about 200 people a day are affected by a severe form of AMD (wet AMD), which can cause severe blindness. 

    These studies show us that while eye care specialists around the world are trying to treat as many patients as possible, unfortunately, many patients are going blind due to delays in diagnosis. However, using advanced AI-based image analysis systems can speed up the detection of warning signs, allowing you to reach more patients.

    One of the advantages of AI for image analysis is its assistance in decision-making. Altris AI is a great example of how an image analysis system can help prevent blindness with AI. The platform allows eye care specialists to detect 74 retina pathologies and pathological signs, including risk conditions for vision loss, like AMD, Diabetic retinopathy, Vascular diseases of the retina, and others. 

    Diagnosing eye disease in children

    AI blindness prevention

    Today, one of the most important AI blindness prevention research is focused on teaching artificial intelligence algorithms to detect retinopathy in premature infants. Retinopathy of prematurity is the main cause of childhood blindness in middle-income countries. Some researches show that around 50,000 children all over the world are blind due to the disease.

    Unfortunately, experts’ forecasts show that these figures are likely to grow. Retinopathy of prematurity is becoming more and more common, especially in African countries. About 30% of children born in sub-Saharan Africa have this disease and, due to late detection and insufficient attention due to the lack of eye care specialists, can also go blind.

    An artificial intelligence model developed by an international team of scientists from the UK, Brazil, Egypt, and the US, with support from leading healthcare institutions, is able to identify children who are at risk of blindness if left untreated. The team of scientists hopes that this AI system will make access to screening and monitoring of young patients more affordable in many regions with limited eye care services and few qualified eye care specialists.

    AI monitors for eye strain control

    Another interesting application of AI to prevent blindness is eye care monitors. They are planned to be used to avoid eye strain due to prolonged computer work. Such monitors will be programmed to monitor the user’s facial expressions, blinks, and eye movements. They will also be able to assess the level of light in the room, and artificial intelligence will automatically adjust the screen brightness and image contrast.

    Since a huge number of the world’s population has switched to remote work since the pandemic and spends almost all day at the computer, such AI monitors are considered a huge help for users in preventing eye diseases that can lead to visual impairment.

    AI to determine better glasses or contact lenses

    AI blindness prevention

    In the field of developing and calculating suitable lenses, there are also a number of companies that have joined the development of AI tools. AI monitors will collect important information about the patient’s eye condition, analyze it, and prescribe suitable contact lenses or glasses. 

    In addition, these monitors will be able to analyze the patient’s medical history, including medical images, and create the most suitable treatment strategy to maximize visual acuity.

    AI for studying the human eye

    AI blindness prevention

    Today, artificial intelligence for low vision is a promising tool for studying human eye tissue and developing new tools for diagnosing and treating eye diseases, including those that lead to vision loss. Artificial intelligence tools are used to analyze OCT images of the eye to detect changes that may indicate diseases such as diabetic retinopathy, macular degeneration, and glaucoma. AI is also used to predict the development of eye diseases based on genetic or risk factors. This is expected to help doctors identify people at risk of developing eye diseases at an early stage and prevent the progression of the disease.

    Summing up

    Today AI for eye diseases is already helping eye care professionals, and some companies, like Altris AI, are already using the potential of artificial intelligence to provide early detection and diagnostic advice for eye care specialists. But it’s worth noting that AI tools are not capable of coming up with innovative solutions for blindness prevention.

    Only in close cooperation with eye care specialists AI blindness prevention tools can help in many ways, like early detection, providing access to medical care in underserved regions, detecting minor or rare conditions, and allowing to focus on personalized care and treatment of patients.

    Disclaimer: USA FDA 510(k) Class II; Altris Image Management System (Altris IMS); AI/ML models and components intended to use for research purposes only, not for clinical diagnosis purposes.

  • OCT eye exam

    5 Tips When Introducing the OCT Eye Exam to Patients

    AI Ophthalmology and Optometry | Altris AI 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. 

    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. 

    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.

    Disclaimer: USA FDA 510(k) Class II; Altris Image Management System (Altris IMS); AI/ML models and components intended to use for research purposes, not for clinical diagnosis purposes.

  • AI for Ophthalmic clinic, photo

    Business Case: Lux Zir and OCT Analysis in Ophthalmic Clinic

    AI Ophthalmology and Optometry | Altris AI Altris Inc.
    11.07.2023
    2 min read

    Business Case: Lux Zir and 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.

    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.

    Disclaimer: USA FDA 510(k) Class II; Altris Image Management System (Altris IMS); AI/ML models and components intended to use for research purposes, not for clinical diagnosis purposes.