title: Combination of Magnetic Resonance Angiography and Computational Fluid Dynamics May Predict the Risk of Stroke in Patients with Asymptomatic Carotid Plaques.
abstract: BACKGROUND Atherosclerosis plaques in the carotid arteries frequently have been found in patients with stroke. However, the pathogenesis of carotid plaque from asymptomatic to cerebrovascular events is a complex process which is still not completely understood. We aimed to investigate the prognosis of asymptomatic carotid atherosclerotic plaques by use of magnetic resonance angiography (MRA) combined with computational fluid dynamics (CFD). MATERIAL AND METHODS We prospectively studied a cohort of 228 participants (mean age 59.21±8.48) with asymptomatic carotid atherosclerotic plaques; mean follow-up duration was 1147.56±224.84 days. Plaque morphology parameters were obtained by MRA analysis. Lumen area (LA) and total vessel area (TVA) were measured, and wall area (WA=TVA-LA) and normalized wall area index (NWI=WA/TVA) were calculated. CFD analysis was performed to evaluate hemodynamic characteristics, including wall pressure (WP) and wall shear stress (WSS). Independent risk factors for stroke were obtained by Cox regression analysis. The area under the curve (AUC) of receiver operator characteristic (ROC) and Z-statistic test were used to evaluate risk factors. RESULTS Logistics regression analysis showed NWI (OR: 3.472, 95% CI: 2.943-4.096, P=0.11) and WSS (OR: 6.974, 95% CI: 1.070-45.453, P=0.42) were independent risk factors of stroke for patients with asymptomatic carotid plaques. The area under the ROC curve values for WSS, NWI, and WSS+NWI were 0.772, 0.798, and 0.903, respectively. CONCLUSIONS The combination of plaque morphology characteristics NWI and hemodynamic parameter WSS may predict the risk of stroke in patients with asymptomatic carotid plaques.
authors.affiliation: Second Department of Geriatric Cardiology, Chinese PLA General Hospital, Beijing, China (mainland).|Department of Cardiology, School of Medicine, Nankai University, Tianjin, China (mainland).
authors.forename: Qian
authors.initials: Q
authors.lastname: Jia
authors.affiliation: Second Department of Geriatric Cardiology, Chinese PLA General Hospital, Beijing, China (mainland).
authors.forename: Hongbin
authors.initials: H
authors.lastname: Liu
authors.affiliation: Second Department of Geriatric Cardiology, Chinese PLA General Hospital, Beijing, China (mainland).|Outpatient Department of North China Military Materials Procurement Bureau, Tianjin, China (mainland).
authors.forename: Yanping
authors.initials: Y
authors.lastname: Li
authors.affiliation: Second Department of Geriatric Cardiology, Chinese PLA General Hospital, Beijing, China (mainland).
authors.forename: Xiaoxi
authors.initials: X
authors.lastname: Wang
authors.affiliation: Department of Cardiology, Jizhong Energy Xingtai Mig General Hospital, Xingtai, Hebei, China (mainland).
authors.forename: Jinju
authors.initials: J
authors.lastname: Jia
authors.affiliation: Department of Radiology, Chinese PLA General Hospital, Beijing, China (mainland).
authors.forename: Yuying
authors.initials: Y
authors.lastname: Li
mesh_terms: D000368:Aged; D001783:Blood Flow Velocity; D002339:Carotid Arteries / Q000000981:diagnostic imaging / Q000473:pathology; D002340:Carotid Artery Diseases / Q000150:complications / Q000000981:diagnostic imaging / Q000473:pathology*; D016893:Carotid Stenosis / Q000150:complications / Q000000981:diagnostic imaging / Q000473:pathology; D005260:Female; D006801:Humans; D018810:Magnetic Resonance Angiography / Q000379:methods; D008297:Male; D008875:Middle Aged; D058226:Plaque, Atherosclerotic / Q000150:complications / Q000000981:diagnostic imaging / Q000473:pathology*; D011237:Predictive Value of Tests; D011446:Prospective Studies; D012307:Risk Factors; D012720:Severity of Illness Index; D020521:Stroke / Q000209:etiology* / Q000473:pathology