Sector-Based Regression Strategies to Reduce Refractive Error-Associated Glaucoma Diagnostic Bias When Using OCT and OCT Angiography

使用OCT和OCT血管造影术诊断青光眼时,基于扇区的回归策略可减少屈光不正相关的诊断偏差。

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Abstract

PURPOSE: This cross-sectional study aimed to investigate the sectoral variance of optical coherence tomography (OCT) and OCT angiography (OCTA) glaucoma diagnostic parameters across eyes with varying degrees of refractive error. METHODS: Healthy participants, including individuals with axial ametropia, enrolled in the Hong Kong FAMILY cohort were imaged using the Avanti/AngioVue OCT/OCTA system. The OCT and OCTA parameters obtained include peripapillary nerve fiber layer thickness (NFLT), peripapillary nerve fiber layer plexus capillary density (NFLP-CD), and macular ganglion cell complex thickness (GCCT). Sectoral measurements of NFLT, NFLP-CD, and GCCT were based on sectors and hemispheres. RESULTS: A total of 1339 eyes from 791 participants were stratified based on spherical equivalent refraction: high myopia (<-6 D), low myopia (-6 D to -1 D), emmetropia (-1 D to 1 D), and hyperopia (>1 D). Multivariable broken stick regression models, accounting for age, sex, and signal strength, showed that all NFLT sectors except temporally, the inferior GCCT hemisphere, and half of the NFLP-CD sectors were more affected by ametropia-related covariates than the corresponding global parameters. As expected, the false-positive rates in those sectors were elevated. Finally, sector-specific axial length (AL) and spherical equivalent (SE) adjustments helped reduce the elevated false-positive rates. CONCLUSIONS: The effect of optical magnification is even more prominent among sectors than the global parameters. AL- and SE-based adjustments should be individualized to each sector to mitigate this magnification bias effectively. TRANSLATIONAL RELEVANCE: Identifying sectoral differences among diagnostic parameters and adopting these sector-based adjustments into commercial OCT systems will hopefully reduce false-positive rates related to refractive error.

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