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Enrichment of Bruch's Membrane from Human Donor Eyes

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OCT Segmentation Errors with Bruch's Membrane Opening-Minimum Rim Width as Compared with Retinal Nerve Fiber Layer

Hongli Yang¹, Jack P Rees¹, Facundo G Sanchez¹

¹Devers Eye Institute Discoveries in Sight Research Laboratories, Legacy Research Institute, Portland, Oregon.

Ophthalmology. Glaucoma

|December 17, 2023

Summary

Automated segmentation errors in glaucoma imaging are common for both Bruch's membrane opening-minimum rim width (BMO-MRW) and retinal nerve fiber layer thickness (RNFLT), with errors not typically occurring in the same location.

Keywords:

Bruch's membrane opening Diagnosis Glaucoma Minimum rim width OCT Retinal nerve fiber layer thickness Segmentation errors

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Area of Science:

Ophthalmology and Optometry
Medical Imaging Analysis

Background:

Accurate measurement of optic nerve head parameters is crucial for glaucoma diagnosis and management.
Automated segmentation algorithms in optical coherence tomography (OCT) are widely used but prone to errors.

Purpose of the Study:

To compare the magnitude and location of automated segmentation errors between Bruch's membrane opening-minimum rim width (BMO-MRW) and retinal nerve fiber layer thickness (RNFLT) measurements.
To assess the impact of these errors on glaucoma classification.

Main Methods:

Cross-sectional study including 162 eyes of glaucoma suspects or patients with open-angle glaucoma.
Spectral-domain OCT imaging was performed, and automated segmentation results for BMO-MRW and RNFLT were exported.
Absolute and proportional errors were calculated globally and by sector, and glaucoma classification differences were analyzed.

Main Results:

Absolute segmentation error was significantly larger for BMO-MRW (10.8 μm) than for RNFLT (3.58 μm), but proportional errors were similar (4.3% vs. 4.4%).
RNFLT errors were associated with specific sectors (superior/inferior), thicker nerve fiber layers, and worse visual fields.
BMO-MRW and RNFLT errors did not commonly occur in the same sector, and manual refinement changed glaucoma classification in 6-8% of eyes.

Conclusions:

Both BMO-MRW and RNFLT measurements exhibit segmentation errors.
These errors do not consistently overlap in location and can potentially influence glaucoma classification.
Understanding segmentation error patterns is important for accurate glaucoma assessment using OCT.