Abstract

Following carotid artery stenting (CAS), new ipsilateral ischemic lesions (NIILs) in the brain are frequently seen using diffusion-weighted imaging (DWI). This study's goal was to identify the imaging characteristics associated with NIILs after CAS by high-resolution magnetic resonance vessel wall imaging (HR-VWI). This was a case-control study. 109 patients who received CAS for atherosclerotic carotid stenosis were retrospectively collected and categorized into NIILs positive and NIILs negative groups. Based on the existence or absence of stroke symptoms after CAS, the NIILs positive group was split into two subgroups: the NIILs symptomatic group and the NIILs asymptomatic group. Patients underwent preoperative HR-VWI and brain magnetic resonance imaging (MRI) within 7 days preoperatively and within 3 days postoperatively. Quantitatively assess carotid plaque burden and components using HR-VWI. The baseline and HR-VWI imaging characteristics of all patients were retrospectively analyzed. To ascertain the imaging characteristics connected with NIILs after CAS, logistic regression analysis was carried out. Among 109 patients, 38 patients (34.9%) developed NIILs after CAS. Six patients (5.5%) developed symptomatic stroke with NIILs. The logistic regression analysis revealed that maximum wall thickness (Max WT) [odds ratio (OR), 1.53; 95% confidence interval (CI): 1.20-1.96; P=0.001], the maximum area percentage of lipid-rich necrotic core (LRNC) (OR, 1.05; 95% CI: 1.03-1.07; P<0.001), the volume of LRNC (OR, 1.004; 95% CI: 1.002-1.005; P<0.001), the maximum area percentage of intraplaque hemorrhage (IPH) (OR, 1.17; 95% CI: 1.11-1.24; P<0.001), the volume of IPH (OR, 1.06; 95% CI: 1.03-1.08; P<0.001), and maximum circumference score of calcification in a single slice (OR, 1.66; 95% CI: 1.04-2.63; P=0.03) were linked with NIILs following CAS. The massive IPH, LRNC, and heavy circumferential calcification were associated with NIILs after CAS. Preoperative quantitative assessment of carotid plaque using HR-VWI may be useful for predicting NIILs following CAS.

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