Combining retinal structural and vascular measurements improves discriminative power for multiple sclerosis patients

Abstract

AbstractData on how retinal structural and vascular parameters jointly influence the diagnostic performance of detection of multiple sclerosis (MS) patients without optic neuritis (MSNON) are lacking. To investigate the diagnostic performance of structural and vascular changes to detect MSNON from controls, we performed a cross‐sectional study of 76 eyes from 51 MS participants and 117 eyes from 71 healthy controls. Retinal macular ganglion cell complex (GCC), retinal nerve fiber layer (RNFL) thicknesses, and capillary densities from the superficial (SCP) and deep capillary plexuses (DCP) were obtained from the Cirrus AngioPlex. The best structural parameter for detecting MS was compensated RNFL from the optic nerve head (AUC = 0.85), followed by GCC from the macula (AUC = 0.79), while the best vascular parameter was the SCP (AUC = 0.66). Combining structural and vascular parameters improved the diagnostic performance for MS detection (AUC = 0.90; p<0.001). Including both structure and vasculature in the joint model considerably improved the discrimination between MSNON and normal controls compared to each parameter separately (p = 0.027). Combining optical coherence tomography (OCT)‐derived structural metrics and vascular measurements from optical coherence tomography angiography (OCTA) improved the detection of MSNON. Further studies may be warranted to evaluate the clinical utility of OCT and OCTA parameters in the prediction of disease progression.