Normative Variability in Retinal Nerve Fiber Layer Thickness: Does It Matter Where the Peaks Are?
Sowjanya Gowrisankaran, Ashkan Abbasi, Xubo Song, Joel S Schuman, Gadi Wollstein, Bhavna J Antony, Hiroshi Ishikawa
Summary
RNFLT-PN reduces normative variability, especially in the ST and IT regions.
Abstract
PURPOSE
Retinal nerve fiber layer thickness (RNFLT), a glaucoma biomarker, has a wide normative range affecting its sensitivity and specificity for abnormality detection. The interindividual RNFLT peak location variability contribution to this wide normative range has not been directly evaluated. The purpose of this study is to assess the effect of RNFLT peak normalization (PN) on normative variability.
METHODS
Circumpapillary RNFLT profiles at 1.7 mm radius from the optic nerve head (ONH) were re-sampled from optical coherence tomography (OCT) volumes (Cirrus HD-OCT, 200 × 200) obtained from one eye of 83 healthy individuals. Fovea-ONH axis (FOA) was calculated from corresponding scanning laser ophthalmoscope images. Supratemporal (ST) and infratemporal (IT) RNFLT peaks of each profile were aligned to respective average peak locations. Normative ranges were calculated by averaging individual profiles before and after PN (with and without FOA to horizontal image axis (HA) alignment).
RESULTS
RNFLT-PN resulted in an overall decrease in coefficient of variation (CoV) of the normative range by 4.2% (P = 0.02). CoV was reduced by more than 10% in clock-hours 10 (11.9%), 8 (10.6%), 6 (10.4%) after PN, and 7 (16.3%), 10 (11.4%), and 12 (10.4%) after PN with FOA-HA alignment. RNFLT-PN corrected for abnormality categorization because of peak misalignment in RNFLT profiles of healthy and glaucoma suspect subjects.
CONCLUSIONS
RNFLT-PN reduces normative variability, especially in the ST and IT regions.
TRANSLATIONAL RELEVANCE
RNFLT-PN reduces normative variability and improves sectoral abnormality categorization, potentially leading to better sensitivity and specificity of RNFLT measure in glaucoma detection.
More by Sowjanya Gowrisankaran
View full profile →Top Research in Diagnosis & Screening
Browse all →Efficacy of a Deep Learning System for Detecting Glaucomatous Optic Neuropathy Based on Color Fundus Photographs.
Dry eye disease and oxidative stress.
Central Corneal Thickness in the Ocular Hypertension Treatment Study (OHTS).
In the Knowledge Library
Discussion
Comments and discussion will appear here in a future update.