Retinal asymmetry in multiple sclerosis

Abstract

The diagnosis of multiple sclerosis is based on a combination of clinical and paraclinical tests. The potential contribution of retinal optical coherence tomography (OCT) has been recognized. We tested the feasibility of OCT measures of retinal asymmetry as a diagnostic test for multiple sclerosis at the community level. In this community-based study of 72 120 subjects, we examined the diagnostic potential of the inter-eye difference of inner retinal OCT data for multiple sclerosis using the UK Biobank data collected at 22 sites between 2007 and 2010. OCT reporting and quality control guidelines were followed. The inter-eye percentage difference (IEPD) and inter-eye absolute difference (IEAD) were calculated for the macular retinal nerve fibre layer (RNFL), ganglion cell inner plexiform layer (GCIPL) complex and ganglion cell complex. Area under the receiver operating characteristic curve (AUROC) comparisons were followed by univariate and multivariable comparisons accounting for a large range of diseases and co-morbidities. Cut-off levels were optimized by ROC and the Youden index. The prevalence of multiple sclerosis was 0.0023 [95% confidence interval (CI) 0.00229–0.00231]. Overall the discriminatory power of diagnosing multiple sclerosis with the IEPD AUROC curve (0.71, 95% CI 0.67–0.76) and IEAD (0.71, 95% CI 0.67–0.75) for the macular GCIPL complex were significantly higher if compared to the macular ganglion cell complex IEPD AUROC curve (0.64, 95% CI 0.59–0.69, P = 0.0017); IEAD AUROC curve (0.63, 95% CI 0.58–0.68, P < 0.0001) and macular RNFL IEPD AUROC curve (0.59, 95% CI 0.54–0.63, P < 0.0001); IEAD AUROC curve (0.55, 95% CI 0.50–0.59, P < 0.0001). Screening sensitivity levels for the macular GCIPL complex IEPD (4% cut-off) were 51.7% and for the IEAD (4 μm cut-off) 43.5%. Specificity levels were 82.8% and 86.8%, respectively. The number of co-morbidities was important. There was a stepwise decrease of the AUROC curve from 0.72 in control subjects to 0.66 in more than nine co-morbidities or presence of neuromyelitis optica spectrum disease. In the multivariable analyses greater age, diabetes mellitus, other eye disease and a non-white ethnic background were relevant confounders. For most interactions, the effect sizes were large (partial ω2 > 0.14) with narrow confidence intervals. In conclusion, the OCT macular GCIPL complex IEPD and IEAD may be considered as supportive measurements for multiple sclerosis diagnostic criteria in a young patient without relevant co-morbidity. The metric does not allow separation of multiple sclerosis from neuromyelitis optica. Retinal OCT imaging is accurate, rapid, non-invasive, widely available and may therefore help to reduce need for invasive and more costly procedures. To be viable, higher sensitivity and specificity levels are needed.

A multi-regression approach to improve optical coherence tomography diagnostic accuracy in multiple sclerosis patients without previous optic neuritis

“…Recent studies have shown intereye difference for pRNFL and mGCIPL can contribute to identifying unilateral optic nerve lesions and this may represent supportive measures for MS diagnosis ( Nolan et al, 2018 , Petzold et al, 2021 ). However, in the current study, the inter-eye absolute difference of pRNFL and mGCC did not improve the detection of MS from healthy controls as compared to the conventional approach.…”

“…However, in the current study, the inter-eye absolute difference of pRNFL and mGCC did not improve the detection of MS from healthy controls as compared to the conventional approach. The limited diagnostic accuracy of retinal asymmetry may be due to study designs (community sample vs clinical sample), patient profiles such as MS disease activity, or co-morbidities ( Petzold et al, 2021 ).…”

Prior Optic Neuritis Detection on Peripapillary Ring Scans using Deep Learning

“…Percentage rather than absolute IOD may be superior over absolute IOD in detecting subtle changes 33 . Clinically meaningful cut-off values may be defined in comparison to healthy controls 20 or based on large reference studies with MS-derived OCT measures 32,34 . Machine learning based classification of eyes with ON history utilizing standard OCT parameters has been promising (Kenney et al in press ).…”

Optical Coherence Tomography in the Differential Diagnosis of Patients with Multiple Sclerosis and Patients with MRI Nonspecific White Matter Lesions

“…In the majority of studies, GCIPL was described as a suitable predictive marker of visual function after ON and neurological deterioration, as measured by the EDSS [66][67][68]. Additionally, in a recently published study [69], the inter-eye difference in GCIPL thickness differentiated MS patients in a large community cohort not only from healthy subjects but also from patients with other diseases. However, there is no information concerning patients with NSWMLs.…”