Joint Analysis of Cardiovascular Control and Shear Wave Elastography to Determine Carotid Plaque Vulnerability

心血管控制与剪切波弹性成像联合分析用于确定颈动脉斑块易损性

阅读:1

Abstract

Background/Objectives: Carotid artery stenosis (CAS) is one of the main causes of stroke, and the vulnerability of plaque has been proved to be a determinant. A joint analysis of shear wave elastography, a radiofrequency echo-based wall tracking technique for arterial stiffness evaluation, and of autonomic and baroreflex function is proposed to noninvasively, preoperatively assess plaque vulnerability in asymptomatic CAS patients scheduled for carotid endarterectomy. Methods: Elastographic markers of arterial stiffness were derived preoperatively in 78 CAS patients (age: 74.2 + 7.7 years, 27 females). Autonomic and baroreflex markers were also assessed by means of an analysis of the beat-to-beat fluctuations in heart period and systolic arterial pressure, derived at rest in supine position (REST) and during active standing. Postoperative analysis identified 36 patients with vulnerable plaque (VULN) and 42 with stable plaque (STABLE). Results: Baroreflex sensitivity (BRS) at a respiratory rate decreased during STAND only in VULN patients, being much higher at REST compared to STABLE levels. Autonomic indexes were not helpful in separating experimental conditions and/or populations. The Young's modulus (YM) of the plaque was lower in the VULN group than in the STABLE one. Cardiovascular control and elastographic markers were significantly correlated only in VULN patients. A multivariate logistic regression model built combining YM and BRS at the respiratory rate improved the prediction of plaque vulnerability, reporting an area under the ROC curve of 0.694. Conclusions: Noninvasive techniques assessing shear wave elastography and baroreflex control could contribute to the early detection of plaque vulnerability in patients with asymptomatic CAS.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。