2022
DOI: 10.1136/jnnp-2022-329680
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Brain age gap in neuromyelitis optica spectrum disorders and multiple sclerosis

Abstract: ObjectiveTo evaluate the clinical significance of deep learning-derived brain age prediction in neuromyelitis optica spectrum disorder (NMOSD) relative to relapsing-remitting multiple sclerosis (RRMS).MethodsThis cohort study used data retrospectively collected from 6 tertiary neurological centres in China between 2009 and 2018. In total, 199 patients with NMOSD and 200 patients with RRMS were studied alongside 269 healthy controls. Clinical follow-up was available in 85 patients with NMOSD and 124 patients wi… Show more

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Cited by 11 publications
(1 citation statement)
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“…The increased node degree of left SMA side predicts the EDSS worsening, further indicating the presence of pseudoadaptive compensation of supplementary motor area, which is consistent with the hypothesis of the increase of node attributes discussed above. In a recent study of deep learning-derived brain age gap base on morphological MRI, the authors reported brain age gap (5.4 (95% CI 4.3 to 6.5) years) significantly predicted EDSS worsening in patients with NMOSD in the 6 tertiary neurological centers of China cohort ( 39 ). Future studies are required to determine the possible causative EDSS worsening factors in individual-scale parameters.…”
Section: Discussionmentioning
confidence: 99%
“…The increased node degree of left SMA side predicts the EDSS worsening, further indicating the presence of pseudoadaptive compensation of supplementary motor area, which is consistent with the hypothesis of the increase of node attributes discussed above. In a recent study of deep learning-derived brain age gap base on morphological MRI, the authors reported brain age gap (5.4 (95% CI 4.3 to 6.5) years) significantly predicted EDSS worsening in patients with NMOSD in the 6 tertiary neurological centers of China cohort ( 39 ). Future studies are required to determine the possible causative EDSS worsening factors in individual-scale parameters.…”
Section: Discussionmentioning
confidence: 99%