# 3D RNFL Structure And High-Resolution Perimetry For Assessing Glaucomatous Damage

> **NIH NIH R01** · TRUSTEES OF INDIANA UNIVERSITY · 2022 · $451,999

## Abstract

7. Project Summary Abstract
Glaucoma is one of the leading causes of preventable blindness, and currently available treatments are not
sufficient to halt progression in many patients. While much has been learned about the biology of glaucoma,
development of new forms of treatment has been stymied by three barriers: high between-subject variability in
ganglion cell number in normal eyes, high within-subject variability for perimetry in patients with glaucoma, and
the slow rate of progression of the disease. The proposed research integrates neural modeling and clinical
research to develop improved methods for diagnosing glaucoma and for assessing progression towards
blindness. The results are intended to improve measures for both clinical trials and ongoing patient care, while
at the same time improving basic science understanding of the pathophysiology of glaucoma and providing
guidance for biological studies of the disease process. Innovative uses of clinical devices will guide testing with
custom systems, and statistical analyses will utilize the synergy between structural and functional measures of
glaucomatous damage. High-resolution retinal imaging of retinal nerve fiber layer (RNFL) will be performed on
patients with glaucoma using a custom advanced adaptive optics scanning laser ophthalmoscope (AOSLO) as
well as custom use of spectral domain optical coherence tomography (SD-OCT). High-resolution perimetry will
be performed in corresponding regions of the visual field, using custom stimuli that are resistant to optical
artifacts that affect conventional perimetry. Specific Aim 1 will determine the role of ganglion cell dysfunction in
between-subject differences in the amount of visual loss corresponding to clinically observed reflectance
defects, and assess longitudinal changes. Specific Aim 2 will utilize the synergy between structural and
functional measures to develop perimetric algorithms that interact dynamically with information about RNFL
structure. Specific Aim 3 will develop methods that dramatically improve the ability to detect wedge defects that
are poorly sampled by conventional perimetry.

## Key facts

- **NIH application ID:** 10368026
- **Project number:** 5R01EY024542-07
- **Recipient organization:** TRUSTEES OF INDIANA UNIVERSITY
- **Principal Investigator:** WILLIAM H. SWANSON
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $451,999
- **Award type:** 5
- **Project period:** 2014-08-01 → 2023-12-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10368026

## Citation

> US National Institutes of Health, RePORTER application 10368026, 3D RNFL Structure And High-Resolution Perimetry For Assessing Glaucomatous Damage (5R01EY024542-07). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10368026. Licensed CC0.

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