A multiple sclerosis (MS) diagnosis often relies upon clinical presentation and qualitative analysis of standard, magnetic resonance brain images. However, the accuracy of MS diagnoses can be improved by utilizing advanced brain imaging methods. We assessed the accuracy of a new neuroimaging marker, visual-evoked cerebral metabolic rate of oxygen (veCMRO₂), in classifying MS patients and closely age- and sex-matched healthy control (HC) participants. MS patients and HCs underwent calibrated functional magnetic resonance imaging (cfMRI) during a visual stimulation task, diffusion tensor imaging, T₁- and T₂-weighted imaging, neuropsychological testing, and completed self-report questionnaires. Using resampling techniques to avoid bias and increase the generalizability of the results, we assessed the accuracy of veCMRO₂ in classifying MS patients and HCs. veCMRO₂ classification accuracy was also examined in the context of other evoked visuofunctional measures, white matter microstructural integrity, lesion-based measures from T₂-weighted imaging, atrophy measures from T₁-weighted imaging, neuropsychological tests, and self-report assays of clinical symptomology. veCMRO₂ was significant and within the top 16% of measures (43 total) in classifying MS status using both within-sample (82% accuracy) and out-of-sample (77% accuracy) observations. High accuracy of veCMRO₂ in classifying MS demonstrated an encouraging first step toward establishing veCMRO₂ as a neurodiagnostic marker of MS.
Keywords: calibrated functional magnetic resonance imaging; diagnosis; metabolism; multiple sclerosis; visual system.