Evaluation of retinal nerve fiber layer progression in glaucoma: a study on optical coherence tomography guided progression analysis.
Leung Christopher Kai-shun, Cheung Carol Yim Lui, Weinreb Robert N, Qiu Kunliang, Liu Shu, Li Haitao, Xu Guihua, Fan Ning, Pang Chi Pui, Tse Kwok Kay
AI Summary
This study showed OCT RNFL thinning rates vary in glaucoma, with faster loss in eyes having thicker baseline RNFL, aiding progression analysis.
Abstract
Purpose
To evaluate optical coherence tomography (OCT) retinal nerve fiber layer thickness (RNFLT) measurement for glaucoma progression analysis.
Methods
One hundred sixteen eyes of 64 patients with glaucoma who were observed within a period of 5 years were included. All eyes had at least four serial RNFL measurements obtained with the Stratus OCT (Carl Zeiss Meditec, Dublin, CA) and with the first and last measurements separated by at least 3 years. Visual field (VF) testing was performed on the same day as RNFL imaging. Serial average RNFLTs were evaluated with guided progression analysis (GPA). VF progression was assessed with trend analysis of the visual field index (VFI). Factors associated with the rate of change in RNFLT were examined with a linear mixed model.
Results
A total of 1101 OCT scans and 1029 VFs were analyzed. Twenty-one and 22 eyes had progression according to RNFL and VF measurements, respectively, and 3 eyes had progression according to both measurements. The rate of change in VFI and RNFLT ranged between -0.5% and -7.2% per year (median loss, -3.0%/y) and between -1.2 and -15.4 microm per year (median loss, -3.3 microm/y), respectively. The sector at seven o'clock (right eye orientation) was the most frequent location that showed progression. A greater baseline RNFLT was associated with an increased rate of reduction of RNFLT (P = 0.034).
Conclusions
OCT GPA offers a new approach to augment glaucoma progression analysis. The rate of RNFLT thinning was variable among patients with glaucoma, with an increased rate of loss in patients with a higher baseline RNFLT.
MeSH Terms
Shields Classification
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