Robotic OCT for automated mapping of outer retinal layer thicknesses

PROJECT SUMMARY This Exploratory/Developmental Research Grant proposal seeks to advance the state of the art in diagnostic ophthalmic imaging with a novel, robotically-aligned optical coherence tomography (OCT) system capable of automatically measuring a retinal biomarker that cannot currently be identified with standard of care OCT devices. Prevention of irreversible vision loss in leading retinal diseases such as diabetic retinopathy (DR) depends on identification of disease changes. While DR has historically been researched and treated as a microvascular complication of diabetes, much less is understood regarding the changes in neurons and photoreceptors in DR. Prior studies in animal models with induced diabetes have demonstrated atrophy in the outer nuclear layer (ONL), which primarily consists of photoreceptor cell bodies. However, the lack of sufficient data in humans means there is still not a widely accepted understanding of the role of photoreceptor loss in DR. OCT is a low coherence interferometric technique that has found widespread adoption in ophthalmology for providing high-resolution, volumetric imaging of the retina. Quantifying changes in the ONL with OCT offers a non-invasive method to follow and understand the course of the photoreceptor degeneration in DR described above. However, conventional OCT systems are not able to discriminate the ONL from Henle’s Fiber Layer (HFL). In order to visualize HFL and therefore isolate the ONL, the pupil entry position of the OCT sample beam must be offset for each individual cross-sectional B-scan. To perform this process volumetrically would require manual adjustment and a great deal of operator time and input. Our research group has pioneered the invention of a robotically-aligned OCT (RAOCT) system capable of imaging both the anterior and posterior eye with active tracking to compensate for subject motion. Our RAOCT system exhibits precise lateral, axial, and angular control of the sample beam and can perform autonomous imaging of freestanding individuals. In the proposed project, we will leverage the micrometer-scale control of the pupil entry position with RAOCT to develop a method for automatically acquiring retinal volumes that provide complete visualization of HFL and the ONL, without the need for operator input. The expected outcome of this proposal is a set of technologies that will provide automated measurements of a retinal biomarker that is otherwise unable to be measured with conventional methods. We expect that our proposed RAOCT system will consistently provide reproducible ONL thickness measurements when accounting for the obscured presence of HFL. We will also demonstrate our device in the clinic in patients with and without diabetic retinopathy. We believe that our results will contribute to our understanding of photoreceptor changes in DR and pave the way for future studies that investigate using ONL thickness measurements to monitor the progression of leading retinal diseases.