# Novel Glaucoma Diagnostics for Structure and Function  - Renewal - 1

> **NIH NIH R01** · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · 2021 · $666,892

## Abstract

Project Summary
Glaucoma is a leading cause of vision morbidity and blindness worldwide. Early disease detection and
sensitive monitoring of progression are crucial to allow timely treatment for preservation of vision. The
introduction of ocular imaging technologies significantly improves these capabilities, but in clinical practice
there are still substantial challenges at certain stages of the disease severity spectrum, specifically in the early
stage and in advanced disease. These difficulties are due to a variety of causes that change over the course of
the disease, including large between-subject variability, inherent measurement variability, image quality,
varying dynamic ranges of measurements, minimal measurable level of tissues, etc. In this proposal, we build
on our long-standing contribution to ocular imaging and propose novel and sensitive means to detect glaucoma
and its progression that are optimized to the various stages of disease severity. We will use information
gathered from visual fields (functional information) and a leading ocular imaging technology – optical
coherence tomography (OCT; structural information) to map the capability of detecting changes across the
entire disease severity spectrum to identify optimal parameters for each stage of the disease. Both commonly
used parameters provided by the technologies and newly developed parameters with good diagnostic potential
will be analyzed. We will use state-of-the-art automated computerized machine learning methods, namely the
deep learning approach, to identify structural features embedded within OCT images that are associated with
glaucoma and its progression without any a priori assumptions. This will provide novel insight into structural
information, and has shown very encouraging preliminary results. We will also utilize a new imaging
technology, the visible light OCT, to generate retinal images with outstanding resolution to extract information
about the oxygen saturation of the tissue. This will provide in-vivo, real time, and noninvasive insight into tissue
functionality. Taken together, this program will advance the use of structural and functional information with a
substantial impact on the clinical management of subjects with glaucoma

## Key facts

- **NIH application ID:** 10222677
- **Project number:** 5R01EY013178-22
- **Recipient organization:** NEW YORK UNIVERSITY SCHOOL OF MEDICINE
- **Principal Investigator:** Joel S Schuman
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $666,892
- **Award type:** 5
- **Project period:** 2000-08-01 → 2024-07-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10222677

## Citation

> US National Institutes of Health, RePORTER application 10222677, Novel Glaucoma Diagnostics for Structure and Function  - Renewal - 1 (5R01EY013178-22). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10222677. Licensed CC0.

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