Test-retest reliability of Cirrus HD-optical coherence tomography retinal layer thickness measurements in people with multiple sclerosis.

Journal: Multiple Sclerosis Journal - Experimental, Translational And Clinical
Published:
Abstract

Optical coherence tomography (OCT) allows evaluation of inter-eye differences (IEDs) in peri-papillary retinal nerve fiber layer (pRNFL) and macular ganglion cell-inner plexiform layer (GCIPL) thicknesses to identify unilateral optic nerve involvement (UONI), which is included in the 2024 revised McDonald diagnostic criteria for multiple sclerosis (MS). To evaluate the test-retest reliability of pRNFL and GCIPL thicknesses/IEDs in people with MS, other neurological disorders, and healthy controls using Cirrus HD-OCT. 509 participants underwent Cirrus HD-OCT, acquiring two macular and optic disc scans per eye within each session. Scans meeting OSCAR-IB quality control criteria were included in final analyses (959 eyes), with no clinical/demographic exclusions (reflecting a real-world clinical setting). Reliability was assessed using coefficients of variation (COVs), intraclass correlation coefficients (ICCs), and Bland-Altman limits of agreement (LOA). IED consistency was evaluated using difference-in-differences (DiDs) of test-retest measurements. GCIPL demonstrated superior reliability (ICC: 0.998, COV: 0.40%, LOA: -1.29 to 1.35 μm) to pRNFL (ICC: 0.989, COV: 1.18%, LOA: -3.59 to 3.70 μm) thickness. Inter-eye absolute DiDs [pRNFL: 2.00 μm (standard deviation (SD) 1.73); GCIPL: 0.64 μm (SD 0.67)] were lower than IED thresholds proposed for identifying UONI. The excellent reliability of GCIPL and pRNFL thicknesses/IEDs support OCT for identifying UONI to diagnose MS.

Authors
Anna Bacchetti, Brenna Mccormack, Ting-yi Lin, Rozita Doosti, Gelareh Ahmadi, Omar Ezzedin, Nicole Pellegrini, Evan Johnson, Anna Kim, Gabriel Otero Duran, Devon Bonair, Elle Lawrence, Ernest Lievers, Simidele Davis, Sooyeon Park, Madeline Inserra, Ananya Gulati, Kathryn Fitzgerald, Elias Sotirchos, Peter Calabresi, Shiv Saidha