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SearchCleveland Clinic inventors have pioneered AI-driven software that analyzes retinal imaging data with unprecedented precision. Led by Justis P. Ehlers, MD, and Sunil Srivastava, MD, this technology extracts critical information from optical coherence tomography scans to enhance disease detection, predict treatment outcomes, and establish new endpoints for clinical trials in ophthalmology.
Cleveland Clinic’s Cole Eye Institute is making strides in ophthalmic care through cutting-edge imaging technology and artificial intelligence (AI) to enhance patient outcomes and advance precision medicine. Led by Justis P. Ehlers, MD, vitreoretinal surgeon, and Sunil Srivastava, MD, retina and uveitis specialist, their innovative work is transforming how eye diseases are detected, monitored, and treated.
Over the past two decades, optical coherence tomography (OCT) and ultra-widefield angiography (UWFA) have become cornerstones of eye care, providing high-resolution cross-sectional images of the retina. Recognizing the untapped potential of this technology, Dr. Ehlers and Dr. Srivastava developed tools that harness AI to analyze these images more precisely and efficiently.
"With these imaging modalities being critical to the everyday management of patients, we realized that there was a wealth of information embedded within those images that we were leaving on the table and our goal was to develop tools that could help unlock that information to be able to make better decisions around patient care and patient management," said Dr. Ehlers.
Initially, the team focused on intraoperative OCT, a technology that offers real-time visualization of microscopic changes during eye surgery. However, they quickly realized its potential extended far beyond the operating room.
“We needed a set of tools to analyze these images,” explained Dr. Srivastava. “That idea became, we need a software package to look at it, which became, we need algorithms that automatically identify the layers of the eye.”
This shift led to the development of AI-driven algorithms capable of analyzing complex retinal images with unprecedented accuracy. These tools are being used on multiple different imaging modalities, from UWFA to OCT, to help develop more enhanced assessments of disease features and characteristics. They can now measure disease progression, predict treatment responses, and personalize patient care in ways previously unimaginable.
A crucial component of the project was ensuring the technology could scale for clinical trials and large datasets. The AI software automates image analysis, providing quantitative insights into disease states and treatment efficacy. A major advantage of these algorithms is that they provide an objective and interpretable output that can be corrected and validated by the end user. This advancement is particularly promising for conditions like diabetic retinopathy and macular degeneration, where early detection and timely intervention are key.
"Some of the major opportunities with these tools are opening new doors to approvable clinical trial endpoints for new therapeutics for managing ophthalmic diseases," added Dr. Ehlers.
The team’s work with these tools is playing a pivotal role in clinical trials. Moving forward, they envision expanding its applications beyond ophthalmology, exploring its potential in detecting systemic diseases through ocular imaging.
"The FDA has said you can use the identification of this layer as an outcome, as a treatment endpoint to determine whether or not your drug will work for dry macular degeneration,” said Dr. Srivastava.
This innovation exemplifies Cleveland Clinic's commitment to harnessing technology for better patient care and represents a significant step toward precision medicine in ophthalmology. As Dr. Ehlers and Dr. Srivastava continue to refine their algorithms and collaborate with industry partners, the future of eye care looks clearer than ever.
For more information about Cleveland Clinic Innovations' digital health technologies, visit here.
