evaluation of visual-evoked cerebral metabolic rate of oxygen as a diagnostic marker in multiple sclerosis

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ID: 149086
2017
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Ranked #27 of 42 articles by views in bulletin of chemical reaction engineering & catalysis

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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.
Reference Key
hubbard2017brainevaluation Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors ;Nicholas A. Hubbard;Yoel Sanchez Araujo;Camila Caballero;Minhui Ouyang;Monroe P. Turner;Lyndahl Himes;Shawheen Faghihahmadabadi;Binu P. Thomas;John Hart;Hao Huang;Darin T. Okuda;Bart Rypma
Journal bulletin of chemical reaction engineering & catalysis
Year 2017
DOI
10.3390/brainsci7060064
URL
http://www.mdpi.com/2076-3425/7/6/64
Keywords
multiple sclerosis diagnosis visual system neuropsychiatry biological psychiatry

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