Comparison of Rates of Progression of Macular OCT Measures in Glaucoma

Abstract

The purpose of this study was to compare rates of change of various macular thickness measures and evaluate the influence of baseline damage on macular rates of change. Methods: One hundred twelve eyes (112 patients) with ≥ 2 years of follow-up and ≥ 5 macular optical coherence tomography (OCT) images and 10-2 visual field (VF) tests were included. OCT measures of interests were full macular thickness (FMT), ganglion cell complex (GCC), ganglion cell/inner plexiform layer (GCIPL), ganglion cell layer (GCL), and outer retinal layer (ORL) thickness in 3°× 3°superpixels. Rates of change were estimated with linear regression and normalized by dividing rates by the average normative superpixel thickness. We compared rates of change and proportion of significantly worsening superpixels (detection rate) and improving superpixels (false discovery rate [FDR]) among macular measures as a function of baseline thickness and 10-2 VF status. Results: Median (interquartile range [IQR]) baseline VF mean deviation, follow-up time, and number of VFs/OCTs were −7.6 dB (−11.8 to −3.8 dB), 4.5 years (4.0-5.0 years), and 9 (8-10), respectively. Normalized FMT and GCC rates of change were faster and detection rates were higher than GCIPL and GCL (P < 0.001), but FMT had lower FDR than GCC (P = 0.02); faster FMT rates were partially explained by ORL rates of change. GCC detection rates were less likely than GCIPL and GCL rates to decrease with diminishing baseline thickness or worse VF damage. In eyes with 10-2 VF worsening, GCC and GCL demonstrated the fastest rates of change. Conclusions: GCC measurements are most likely to detect structural worsening along the spectrum of glaucoma severity. Although FMT rates of change are least influenced by baseline thickness, they partially reflect likely age-related ORL changes. Translational Relevance: GCC thickness measurements seem to be the optimal macular outcome measure for detection of glaucoma deterioration.

Estimating Ganglion Cell Complex Rates of Change With Bayesian Hierarchical Models

“…Therefore, we kept as much as possible of valid data to provide accurate results from the model. We recently reported that GCC is potentially the optimal inner macular parameter for detection of glaucoma progression across the spectrum of glaucoma severity, 4,20 and thus we used GCC as the macular outcome of interest for this study.…”

“…Superpixels or even clusters of superpixels across the macula are correlated, with the correlation being a function of physical or physiologic distance between the superpixels. 20 We analyzed data for each superpixel separately. This made the modeling easier, at a cost of not allowing us to borrow strength from neighboring superpixels to better estimate trends at each superpixel and preventing us from making joint statements about individual trends across superpixels.…”

“…Recent research has suggested that the superpixels in which measurements behave similarly are not just neighbors but may belong to differently shaped nonconvex clusters. 20 Similarly, random intercepts, random slopes, and random errors may have complex spatial associations not easily modeled by local spatial autocorrelation models. Our future work will consider spatial location and physiologic relationships of superpixels (clusters) in expanded Bayesian hierarchical models.…”

“…Hence, estimating macular thickness changes in smaller areas such as 3°× 3°superpixels is of interest. 4,[18][19][20][21][22][23] Miraftabi et al 24 reported that repeated thickness measurements across the macula at the level of 3°× 3°superpixels demonstrated a low and uniform within-session variability. Nouri-Mahdavi et al 25 recently showed that between-session variability of local inner retinal thickness measurements was very low and that most of the total between-session variability could be explained by within-session variability.…”

“…While measurement of change in localized areas of the macula is essential for detecting local changes, there is a significant correlation between thickness measurements and thickness changes in physically or physiologically adjacent regions of the macula. 20 A hierarchical approach, once fully developed, can address the varying behavior of superpixels across the macular region while at the same time taking into account any potential correlations in rates of change or their variance among superpixels of varying sizes.…”