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• W4386945784 abstract "The difficulty of recanalization for intracranial atherosclerosis–related large vessel occlusion (ICAS-LVO) is closely related to the severity of stenosis. This study sought to investigate the characteristics of enhancement based on high-resolution magnetic resonance imaging (HR-MRI) so as to judge the severity of stenosis. Sixty-two patients with symptomatic ICAS-LVOs who underwent endovascular treatment were prospectively recruited for HR-MRI (33 patients with severe stenosis and 29 without). The diagnostic agreements in locating occlusion segments were assessed between HR-MRI and angiographic assessment. The severity of atherosclerotic stenosis was evaluated by enhancement grade and quantitative enhancement index. Univariate and multivariate analyses were used to identify the parameters associated with the severity of stenosis. HR-MRI showed good agreement with angiographic assessments for evaluating the occlusion site (κ=0.97) and length (concordance correlation coefficient=0.70). Compared with patients without severe stenosis, patients with severe stenosis exhibited higher enhancement index (0.69 versus 0.19; p< 0.001) of occlusion segments. In multivariate analysis, the enhancement index was an independent factor associated with the severity of stenosis (OR =2.92; 95% CI, 1.60–5.34, p< 0.001). The enhancement index had an AUC of 0.89, with a sensitivity of 76.0% and a specificity of 86.0%. The model fit improved when including the enhancement index (AUC= 0.93 versus 0.72). All of patients with severe stenosis required additional rescue treatments, which have a longer procedural time (104.0 versus 91.0 minutes; p= 0.002). Higher enhancement index of occlusion segments was associated with the severe atherosclerotic stenosis." @default.
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• W4386945784 date "2023-09-01" @default.
• W4386945784 modified "2023-10-17" @default.
• W4386945784 title "Significant Enhancement of Occluded Segment on Magnetic Resonance Imaging Predicts Severe Stenosis in Atherosclerotic Occlusion" @default.
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• W4386945784 doi "https://doi.org/10.1016/j.metrad.2023.100021" @default.
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