Abstract
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.
Highlights
Current procedures for diagnosing multiple sclerosis (MS) rely primarily upon clinical presentation and qualitative analysis of standard, medical-grade magnetic resonance structural, brain images, e.g., [1]
We tested whether MS patients differed in their cerebral blood flow (CBF) response to the CO2 solution ((CBFhc −CBF0 )/CBF0 ) and M in their respective gas challenge region of interest (ROI) within occipital lobe see [87]
MS patients (3.88 ± 0.48%) did not significantly differ in M compared to healthy control (HC) (5.11 ± 0.39%), t(18.90) = −1.98, p = 0.062
Summary
Current procedures for diagnosing multiple sclerosis (MS) rely primarily upon clinical presentation and qualitative analysis of standard, medical-grade (e.g., lower resolution) magnetic resonance structural, brain images, e.g., [1]. It has been demonstrated that the diagnostic accuracy of MS can be improved when providers implement advanced neuroimaging techniques and analyses that are not presently common in clinical practice, e.g., [2], see [3]. We investigated the accuracy of an advanced neuroimaging technique never before used in MS, calibrated functional magnetic resonance imaging (cfMRI), to classify MS patients and closely age- and sex-matched healthy controls (HCs). We focused our analyses upon the ability of a new neuroimaging marker, visual-evoked cerebral metabolic rate of oxygen (veCMRO2 ), to accurately discriminate between MS patients and HCs. cfMRI is a relatively new neuroimaging technique that capitalizes upon established relationships between blood-oxygen-level dependent (BOLD) signal and cerebral blood flow (CBF) in order to estimate steady-state, oxygen metabolism [6,7] see [8]. The CMRO2 metric permitted by cfMRI offers several advantages over the more commonly used BOLD signal
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