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基于临床图像的患者特异性主动脉瓣二叶瓣叶和三叶瓣叶形态的定量分析。

Patient-Specific Quantification of Normal and Bicuspid Aortic Valve Leaflet Deformations from Clinically Derived Images.

机构信息

James T. Willerson Center for Cardiovascular Modeling and Simulation, Oden Institute for Computational Engineering and Sciences, Department of Biomedical Engineering, The University of Texas at Austin, Austin, TX, 78712, USA.

Gorman Cardiovascular Research Group, Smilow Center for Translational Research, Department of Surgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA.

出版信息

Ann Biomed Eng. 2022 Jan;50(1):1-15. doi: 10.1007/s10439-021-02882-0. Epub 2022 Jan 7.

Abstract

The clinical benefit of patient-specific modeling of heart valve disease remains an unrealized goal, often a result of our limited understanding of the in vivo milieu. This is particularly true in assessing bicuspid aortic valve (BAV) disease, the most common cardiac congenital defect in humans, which leads to premature and severe aortic stenosis or insufficiency (AS/AI). However, assessment of BAV risk for AS/AI on a patient-specific basis is hampered by the substantial degree of anatomic and functional variations that remain largely unknown. The present study was undertaken to utilize a noninvasive computational pipeline ( https://doi.org/10.1002/cnm.3142 ) that directly yields local heart valve leaflet deformation information using patient-specific real-time three-dimensional echocardiographic imaging (rt-3DE) data. Imaging data was collected for patients with normal tricuspid aortic valve (TAV, [Formula: see text]) and those with BAV ([Formula: see text] with fused left and right coronary leaflets and [Formula: see text] with fused right and non-coronary leaflets), from which the medial surface of each leaflet was extracted. The resulting deformation analysis resulted in, for the first time, quantified differences between the in vivo functional deformations of the TAV and BAV leaflets. Our approach was able to capture the complex, heterogeneous surface deformation fields in both TAV and BAV leaflets. We were able to identify and quantify differences in stretch patterns between leaflet types, and found in particular that stretches experienced by BAV leaflets during closure differ from those of TAV leaflets in terms of both heterogeneity as well as overall magnitude. Deformation is a key parameter in the clinical assessment of valvular function, and serves as a direct means to determine regional variations in structure and function. This study is an essential step toward patient-specific assessment of BAV based on correlating leaflet deformation and AS/AI progression, as it provides a means for assessing patient-specific stretch patterns.

摘要

心脏瓣膜疾病的个体化建模的临床获益仍然是一个未实现的目标,这通常是由于我们对体内环境的理解有限所致。在评估最常见的人类心脏先天性缺陷二叶式主动脉瓣(BAV)疾病时尤其如此,这种疾病会导致主动脉瓣狭窄或关闭不全(AS/AI)提前且严重。然而,由于解剖和功能变异程度很大,在很大程度上尚不清楚,因此基于患者个体评估 BAV 发生 AS/AI 的风险受到了阻碍。本研究旨在利用一种非侵入性的计算管道(https://doi.org/10.1002/cnm.3142),该管道直接使用患者特定的实时三维超声心动图(rt-3DE)数据生成局部心脏瓣膜叶变形信息。从患有正常三尖瓣主动脉瓣(TAV,[Formula: see text])和 BAV([Formula: see text]融合的左和右冠状动脉瓣和[Formula: see text]融合的右和非冠状动脉瓣)的患者中收集了成像数据,从中提取了每个瓣叶的中面。首次对 TAV 和 BAV 瓣叶的体内功能变形进行了量化差异的分析。我们的方法能够捕获 TAV 和 BAV 瓣叶中复杂的、异质的表面变形场。我们能够识别并量化瓣叶类型之间的拉伸模式差异,特别是发现 BAV 瓣叶在关闭过程中经历的拉伸与 TAV 瓣叶在异质性和整体幅度方面都不同。变形是评估瓣膜功能的临床评估中的关键参数,是确定结构和功能区域变化的直接手段。这项研究是基于瓣叶变形与 AS/AI 进展相关联对 BAV 进行个体化评估的重要步骤,因为它提供了一种评估患者特定拉伸模式的方法。

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