Optical coherence tomography-measured retinal nerve fiber layer thickness values compensated with a multivariate model and discrimination between stable and progressing glaucoma suspects

Hemma Resch,Florian Frommlet,Philipp Fuchs,Florian Schwarzhans,Anton Hommer,Clemens Vass

doi:10.1007/s00417-021-05329-3

Abstract

PurposeOur previously introduced multivariate model, compensating for intersubject variability, was applied to circumpapillary retinal nerve fiber layer (RNFL) values measured with optical coherence tomography in glaucoma suspects with or without prior progressive optic disc (OD) change in a series of confocal scanning laser tomography (CSLT, HRT III) measurements.MethodsIn this prospective study, OD change during CSLT follow-up was determined with strict, moderate, and liberal criteria of the topographic change analysis (TCA). Model compensation (MC) as well as age compensation (AC) was applied to RNFL sectors (RNFLMC vs. RNFLAC). Diagnostic performance of RNFLMC vs. RNFLAC was tested with an area under the receiver operating characteristic (AUROC) and was compared between methods.ResultsForty-two glaucoma suspects were included. Patients without prior progressive OD change during the CSLT follow-up (= stable) had thicker RNFL thickness values in most areas and for all progression criteria. RNFLMC AUROC for the global RNFL (0.719) and the inferior quadrant (0.711) performed significantly better compared with RNFLAC AUROC (0.594 and 0.631) to discriminate between stable and progressive glaucoma suspects as defined by the moderate criteria of CSLT progression analysis (p = 0.028; p = 0.024).ConclusionMC showed a slight but significant improvement in detection of subjects with prior progressive OD change among a group of glaucoma suspects, when compared to AC, which is the compensation method commonly used during OCT data evaluation in daily routine. Further studies are warranted to validate the present results.

Highlights

Glaucoma is a progressive optic neuropathy characterized by the irreversible loss of retinal ganglion cells and their axons, leading to visual field defects [1]
We use our prior published multivariate model that facilitates a clinically meaningful reduction of the intersubject variance of peripapillary retinal nerve fiber layer (RNFL) parameters, by compensating for variation of parameters correlating with RNFL thickness distribution
This model includes physiological parameters, automatically extracted from optical coherence tomography (OCT) fundus images such as retinal vessel density, optic disc (OD) shape, fovea location, and age and refractive error [23, 24]. This model (MC) was applied on RNFL parameters measured with Cirrus OCT in patients with suspicion of glaucoma

Summary

Introduction

Glaucoma is a progressive optic neuropathy characterized by the irreversible loss of retinal ganglion cells and their axons, leading to visual field defects [1]. Early diagnosis of glaucoma, besides functional tests, is performed based on imaging techniques such as optical coherence tomography (OCT) [2] This is done by measuring the circumpapillary retinal nerve fiber layer (RNFL) thickness and optic disc (OD) parameters and comparing the measurement results with a normative database. Despite a high reproducibility [3, 4] of RNFL thickness measurements, intersubject variance [5] due to the influence of numerous individual factors hampers the interpretation and use of imaging techniques, especially in the early diagnosis of glaucoma Individual biomarkers, such as sex, age, and ethnicity [6,7,8,9], are typically taken into account by the normative databases. Other factors are not, including optic disc and fovea parameters, retinal vessel position, axial length, and refractive error, they show an association with circumpapillary RNFL thickness and distribution [10,11,12,13,14,15,16,17,18,19]

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