Optical Coherence Tomography (OCT) has transformed eye care and is being developed in several medical specialties. But what will it take to improve public health, to detect and manage hidden disease at earlier and more treatable stages? Dr. James Fujimoto, alongside clinician-scientists Dr. Michael Abramoff and Dr. Hiroyuki Takahashi, and industry leader Mr. Ali Tafreshi, shared insights on advancing OCT into broader medical practice.

Today, OCT is already indispensable in eye care. “Allvar Gullstrand, who won the Nobel Prize for inventing the fundus camera, never saw the clinical impact of his work. In contrast, Dr. Fujimoto, who developed OCT, is witnessing the global transformation sparked by OCT in his lifetime.” (Dr. Michael Abramoff) OCT has become a clinical standard for detecting and managing sight impairing diseases such as diabetic retinopathy, age related macular degeneration, and glaucoma. It is also an emerging modality in other specialties such as cardiology and surgical guidance. However, the most impactful advances promise to be in public health. Noninvasive imaging of the eye can evaluate not only eye diseases, but also systemic conditions like diabetes, cardiovascular disease and vasculopathy, including heart attack and stroke risk, and neurodegenerative diseases like Alzheimer’s and Parkinson’s disease. The aim is to build an easily accessible, datadriven healthcare system that detects chronic diseases at early, treatable stages, supported by streamlined care coordination, with the ultimate goal of improving quality of life, while reducing healthcare costs. This panel brings together a team of experts to discuss how the eye can enable primary care and systemic disease detection through easily accessible, AI-powered imaging.

In Japan, it is easy to gain access to medical specialists thanks to the national health insurance (NHI) system which covers all citizens. OCT examinations are also covered by the NHI, and costs incurred by medical institutions are reimbursed according to the NHI points system. Also, many corporations, schools, and local governments offer regular health examinations. However, eye checkups are optional, and therefore people tend not to take them regularly. In the U.S., OCT is commonly used in ophthalmology and optometry, with FDA-approved devices and insurance-based coverage and reimbursement. As Doctor Hiroyuki Takahashi and Mr. Ali Tafreshi emphasized OCT offers two critical advantages: (1) it is non-invasive and comfortable for patients, so exams can be performed in an office setting, and (2) it provides objective, quantitative data on retinal microstructure. Dr. Abramoff who played a key role in developing AI diagnostic systems added that OCT’s success lies in this objectivity and the fact that treatment outcomes using OCT imaging have been shown to be superior to those without it.

Dr. Fujimoto posed a question: “What must we do to expand OCT beyond eye care and drive meaningful healthcare advances?” Mr. Tafreshi advocated for a cloud-based infrastructure that links imaging data to health outcomes. Mr. Takahashi pointed to automation and digital patient IDs as critical enablers. All agreed that ensuring trust, regulatory clearance for new use cases outside of eye care, and reimbursement policies will be essential. Ultimately, this requires proving that using OCT retinal imaging to identify and monitor the treatment of systemic diseases improves patient outcomes. This is why population level scaling and accumulating real-world OCT data from routine screenings is critical. Over the past two decades, OCT has become widely adopted, and the advent of robotic diagnostic systems has made it possible to deliver OCT exams seamlessly. Dr. Abramoff noted that the resulting data volume now allows for true, real-world measurements, not just estimates, of disease incidence and prevalence, as well as precise predictions about outcomes of the disease. The conversation grew more animated from there.

Takahashi :　OCT examinations are widely accepted because they’re so patient friendly. With further automation, these exams can be as routine as taking a patient’s blood pressure or temperature, in places ranging from frontline care clinics, optical shops, schools, and workplaces. Thus, large-scale data collection provides critical information about public health, which will allow even better AI diagnosis and disease management.

Tafreshi : 　Extending AI enabled OCT beyond eye care would be a major leap for healthcare. It is non-invasive, scalable, and could rival or even surpass population-level blood or genetic screening in terms of reach and diagnostic potential.

Abramoff : 　Beyond eye care, I believe general medicine will become the largest market for retinal OCT imaging. Still, disease management through eye care professionals will remain a crucial entry point.

Fujimoto : 　Dr. Abramoff, you led the development of the first FDA-approved autonomous AI retinal imaging to diagnose diabetic retinopathy. How did you demonstrate that it could reduce healthcare costs?

Abramoff : 　We built on decades of clinical evidence showing that treating diabetic retinopathy at the right stage improves outcomes. With that foundation, we only needed to prove (in randomized controlled trials) that autonomous AI does this more accurately and efficiently, at lower cost, and ultimately achieves better outcomes for patients.

Fujimoto : 　Measuring systemic complications from diabetes, such as neurological damage or kidney impairment, is particularly challenging.

Abramoff: 　What diabetic patients fear most is vision loss. There is research that shows reporting the possibility of vision impairment following the examination helped patients to change their lifestyles for the better, which in turn improved their kidney functioning.

Tafreshi : 　We need to position OCT as a tool for ongoing health monitoring and preventive care for every patient, including patients not receiving eye care. It offers a unique, non-invasive window into the brain, heart, and vascular system at micron resolution. In Japan, where annual health checkups are common, OCT could be incorporated into these screenings, as simple as taking blood pressure, creating a valuable dataset for both research and patient care, globally.

Takahashi : 　With diagnostic AI, a single OCT scan could reveal much more: retinal diseases, choroidal conditions, even age-related changes. If we expand how we interpret the massive amounts of information available from the eye, we could unlock insights into a wide range of systemic diseases.

Tafreshi : 　I fully agree with you. We need an integrated system where individuals are invited for health screening, and if flagged, they are referred to the appropriate specialist, that could be an eye care provider, cardiologist, or nephrologist. We can combine AI and OCT to continuously gather data and enable timely, targeted referrals.

Fujimoto : 　AI-enabled triage and referral will be key. While FDA or other regulatory agencies are strict when it comes to AI diagnostics, the technology is well suited for prescreening, helping identify who needs further evaluation. It could significantly expand the front door to healthcare.

Fujimoto :　One of the main challenges we face is balancing sensitivity and specificity. If specificity is too low, we risk overwhelming the healthcare system with false positives, leading to unnecessary costs and burden. It is a delicate trade-off.

Tafreshi :　The key is longitudinal tracking. If we combine AI with OCT and perform scans every few months, we can identify meaningful changes over time and reduce false positives.

Fujimoto :　Glaucoma is a good example. It’ s a leading cause of irreversible blindness, yet population-level variation makes it hard to detect early. But by tracking individual changes over time, we can catch the disease before it progresses. Frequent imaging is essential.

Abramoff :　Adoption will ultimately depend on having a compelling clinical use case, one that outperforms existing methods, leads to better outcomes, and can be delivered at scale. Alzheimer’s is a good example. OCT can detect it earlier and more reliably than memory tests, but the memory test is cheaper. Someone must take the risk to generate the data and prove OCT’s value in these contexts.

Tafreshi :　Cost is still a barrier. What if we created a low-cost OCT screening service focused on preventive care? Anyone walking into a frontline care setting, retail store, optical shop, or community care clinic could receive a scan, increasing access and return on investment for OCT systems.

Takahashi :If schools and companies set up OCT rooms for employees or students, it would benefit both organizations and individuals by promoting routine health monitoring.

Fujimoto :　OCT provides comprehensive quantitative information, but historically it required medical specialists to interpret OCT data, which limited its scalability. If AI can analyze longitudinal data with a practical balance of sensitivity and specificity, it could significantly improve scalability.

Abramoff :　AI can already detect and quantify a variety of biomarkers in retinal fundus images. Patient variability isn’t an issue as long as we’re focused on detecting change within individuals over time.

Tafreshi :　That’s why we should build a benchmark database, starting with fundus images for general checkups, then incorporating OCT for monitoring and prognostics, as well as clinical and outcome data. This would create a foundation for scalable, AI-driven screening and management.

Abramoff :　Exactly. I love OCT, but due to its wavelength limitations, we can’t visualize blood containing structures the way we can with fundus imaging. Fundus images are still incredibly valuable. That is also why Topcon’s Maestro combining OCT and fundus imaging in one patient friendly setting has been so exciting.

Tafreshi :　The pace of AI development is accelerating. If we don’t roll out OCT services to enhance the wave created with fundus imaging within the next three to five years, we risk losing momentum. Regulators, payers, clinicians, and tech companies must align under a shared mission. This is not the time for competition.

Abramoff :　Every day we wait, patients are losing vision or worse. We must act. We have to create a collaboration to engage U.S. payers and the FDA. We need to take the risk and present compelling data to drive this forward.

Fujimoto :　OCT can detect diabetes and other silent systemic diseases through the eyes. It’s clearly a powerful tool for advancing healthcare goals. The challenge lies in transforming primary care delivery models and building viable business plans to support them. Success will depend on how many people we need to screen to find meaningful cases, but the potential is strong.

Abramoff :　Show me better outcomes, and I’ll take it to the payers. Ali and his team are doing a great job, and I’m ready to support this effort however I can.

Tafreshi :　We have a deal!

Takahashi :　Research strengthens clinical skills, and clinical experience, in turn, enriches research. The two are deeply synergistic. That’s why I strongly encourage the younger members of my team to collaborate with ophthalmologists and fellow researchers across disciplines.

Tafreshi :　How is the bonded magnet that I developed used now?

Iriyama :　“Data is king” and its influence is only growing. In the U.S., people typically see eye care providers early and often, especially for vision correction. As a result, OCT exams are generating one of the richest and most underutilized health datasets in the world. I encourage the next generation to explore ophthalmic OCT as a powerful research frontier.

Abramoff :　OCT retinal imaging offers a unique and non-invasive window into the brain, something few other methods can achieve. It’s also incredibly patient-friendly. Young researchers entering this field can contribute meaningfully to the health of millions. This is a challenge worth committing to fully.

Tafreshi :　How is the bonded magnet that I developed used now?

Fujimoto :　It’s important to remember that scientific or clinical advancement doesn’t happen in isolation. Progress requires multidisciplinary teamwork spanning medicine, engineering, data science, business, and policy. We need collaboration and mutual understanding across all these domains. Investment at this scale demands both courage and conviction. But the passionate people in this space are deeply committed and history shows that true progress always comes from those who believe in their goals.