Detecting Glaucomatous Progression With a Region-of-Interest Approach on Optical Coherence Tomography: A Signal-to-Noise Evaluation

PURPOSE: To compare two region-of-interest (ROI) approaches and a global thickness approach for capturing progressive circumpapillary retinal nerve fiber layer (cpRNFL) changes on optical coherence tomography (OCT) imaging. METHODS: Progressive cpRNFL thickness changes were evaluated in 164 eyes with a clinical diagnosis of glaucoma or suspected glaucoma; all eyes underwent optic disc OCT imaging on two visits at least 1 year apart. Such changes were evaluated with a manual ROI approach (ROI(M)), which involved manual identification of region(s) of observed or suspected glaucomatous damage. The ROI(M) was compared with an automatic ROI approach (ROI(A)), where regions were automatically identified if the cpRNFL thickness fell below the 1% lower normative limits, and to global cpRNFL thickness. These methods were compared using longitudinal signal-to-noise ratios (SNRs), calculated based upon individualized estimates of measurement variability and age-related changes for each ROI, obtained from 321 glaucoma eyes and 394 healthy eyes, respectively. RESULTS: The average longitudinal SNR of the ROI(M), ROI(A) and global thickness methods were −0.46, −0.39, and −0.30 y(−1), respectively. The average longitudinal SNR for the ROI(M) was significantly more negative compared with both the ROI(A) and global thickness methods (P = 0.005 for both). CONCLUSIONS: A manual ROI approach was the optimal method for detecting progressive cpRNFL loss compared with an automatic ROI approach and the global cpRNFL thickness measure. TRANSLATIONAL RELEVANCE: These findings highlight the potential advantages conferred by a careful qualitative evaluation of OCT imaging for detecting glaucoma progression.