SBIR-STTR Award

Our goal is to develop and validate a device-independent software application for analysis of optical coherence tomography (OCT) images of the human retina. Our system will make quantitative measurements of retinal layer thicknesses at the macula in support of the generation of biomarkers for measuring onset and progression of ocular and neurodegenerative diseases, including age-related macular degeneration (AMD), diabetic retinopathy (DR), glaucoma, multiple sclerosis (MS), Alzheimer’s disease, Parkinson’s disease, and amytrophic lateral sclerosis (ALS). Retinal layer thicknesses indicate atrophy through thinning and increased fluid or inflammation through thickening. Accurate, device-independent segmentation of retinal layers together with longitudinal analysis of the layer thicknesses can return a number of quantitative biomarkers to correlate with disease onset and progression, and facilitate direct comparison across OCT devices to results from normal to estimate the degree of abnormalities. Specifically, we are aiming to: Aim 1 – Improve our segmentation of diseased eyes Orion (www.voxeleron.com/orion), our current research platform has been validated and used extensively on normal, non-pathologic eyes. Our structural analyses of retinal layers may be complicated, however, by ocular diseases or opacities prevalent in an aging population. Current software, ours included, can perform poorly in the case of disease, a situation we aim to ameliorate by improving our current segmentation algorithm in these cases and validating its performance on a large, hand-segmented dataset including AMD, DR, and glaucoma cases taken from at least 4 different device manufacturers’ OCT cameras. Aim 2 – Add longitudinal analysis to our segmentation software Clinically, static analysis of data has limited utility. We will add longitudinal analysis to our existing segmentation capabilities to measure the change of thicknesses over time. This new clinical workstation will be rigorously tested by determining agreement with expert-generated ground-truth.

Public Health Relevance Statement:
NARRATIVE: This project will establish an image analysis software platform to automatically process optical coherence tomography images of the human retina. This platform will provide the first device-independent and commercially available software that can perform analyses, static or longitudinal, on the thicknesses of the layers of the retina directly associated with photo-receptor and neuronal degeneration. As such, it will accelerate the pace of discovery and understanding in both ocular and neurodegenerative diseases, and facilitate the development of clinical biomarkers for diseases such as age-related macular degeneration, diabetic retinopathy, glaucoma, Alzheimer’s, Parkinson’s, multiple sclerosis, and amyotrophic lateral sclerosis that affect millions of Americans.

Project Terms:
adaptive optics; Affect; Age related macular degeneration; aging population; Agreement; Algorithms; Alzheimer's Disease; American; Amyotrophic Lateral Sclerosis; Anatomy; Angiography; Atrophic; Auras; Belief; Biological Markers; brain health; Central Nervous System Diseases; Clinical; clinical application; clinical biomarkers; clinical development; Clinical Research; clinically relevant; cloud based; commercialization; Complex; Computer software; Cyst; Data; Data Analyses; Data Set; Databases; Development; Devices; Diabetic Retinopathy; Diagnosis; Disease; Disease Management; Edema; Ensure; Epiretinal Membrane; Eye diseases; fovea centralis; ganglion cell; Ganglion Cell Layer; Generations; Glaucoma; Goals; Growth; Hand; human imaging; Image; Image Analysis; image registration; improved; Individual; Industry; Inflammation; Inflammatory; Inner Plexiform Layer; interest; Liquid substance; longitudinal analysis; longitudinal dataset; macula; Manuals; Manufacturer Name; Measurement; Measures; meetings; Methods; Modality; Monitor; Multiple Sclerosis; Nerve Degeneration; nervous system disorder; Neuraxis; Neurodegenerative Disorders; Nuclear; Observational Study; Ocular Pathology; Onset of illness; Ophthalmology; Optical Coherence Tomography; Outcome; parallelization; Parkinson Disease; Pathologic; Pathology; Patients; Performance; Phase; photoreceptor degeneration; Physicians; Primary Lateral Sclerosis; Process; receptor; Reporting; Research; Research Personnel; Resolution; Retina; Retinal; Retinal Diseases; Scanning; Scientist; Slice; software development; standard of care; System; Techniques; Technology; Testing; theories; Thick; Thinness; Three-Dimensional Image; Time; tool; Uveitis; Work

Ophthalmic imaging is of critical importance to ocular disease management and, increasingly, as a window toneurodegenerative and systemic diseases. Optical coherence tomography (OCT) is its most important modality, but alsoits most problematic in terms of interoperability, storage and unified analyses. Much of this is to do with incompatibleinstruments and data formats. Rapid advances in radiology resulted from the DICOM standardization of image data,facilitating more collaborative work, better data insight, device independence and innovative developments that todayhave spawned multiple independent vendors offering processing and archival solutions. For OCT, no such solution existsand, as a direct result, despite being the standard of care, the clinical data remains under-utilized and the researchfragmented. Open formats reduce overall costs and can ultimately lead to better patient outcomes.This project will establish the first, commercial grade, cloud-based, truly vendor neutral, DICOM compliant, image andinformation storage and processing platform for ophthalmic OCT. The proposed system will bring the functionality,interoperability, and innovation of radiology to ophthalmology. The project has the following clear and achievablemilestones: 1) Develop Nebula, a cloud-based, DICOM-compliant, image storage and archive platform. This will be builtwith security as the primary consideration and will natively support patient management systems. 2) Add a web-basedanalysis front-end to Nebula optimized for clinical ophthalmic workflows. 3) Build on our Phase I award, and implement,validate and release AI-based AMD prognostics, OCT-angiography analytics and retinal fluid quantification software. 4)Apply for regulatory approval for both Nebula's picture archiving and communications (PACS) for ophthalmology and thefluid quantification module. This will allow for clinical use of the system and serve as a platform for a wide variety ofophthalmic and neurologic research.We have received significant interest in the proposed work from researchers, ophthalmologists, and optometrists. And,toward these ends, we have assembled a team of experts to manage, implement, validate, and release this software. Thatis, to achieve all the aims presented.

Public Health Relevance Statement:
NARRATIVE: This project will build the first cloud-based, truly vendor neutral, DICOM compliant, image and information storage and processing platform for ophthalmic optical coherence tomography (OCT) imagery. It will bring the functionality, interoperability, and AI-enabled innovation of radiology to ophthalmology. It will speed up the pace of innovation, support telemedicine, and, ultimately, offer better patient outcomes for diseases such as AMD, diabetic retinopathy, glaucoma, Alzheimer's, Parkinson's, and MS - diseases that affect millions of Americans.

Project Terms: