Probabilistic Modeling of Stenotic Aortic Valve Intervention

描述(申请人提供)：项目摘要/摘要：主动脉瓣狭窄是西方世界最常见的心脏瓣膜疾病，随着人口老龄化，其患病率也在增加。目前首选的治疗方法是用外科植入的人工瓣膜进行完整的瓣膜置换。然而，对于高龄和合并疾病的高危患者，手术死亡率会上升。近年来，微创经导管主动脉瓣置入术(TAV)作为外科瓣膜置换术的一种腔内替代方法已被研究。虽然已经获得了重要的经验，但TAV植入的临床试验也与并发症有关，如装置移位、瓣膜旁渗漏、冠脉阻塞和入路部位损伤。此外，TAV假体的长期耐用性和安全性在很大程度上是未知的，必须仔细评估和研究。为了对TAV介入治疗中涉及的生物力学有一个定量的了解，本项目的目标是开发概率计算模型来研究不同患者条件下的主动脉组织-TAV结构相互作用和血流动力学，并为TAV患者筛选和TAV设计改进提供科学依据。为了实现这些目标，提出了以下具体目标：1)通过对50例人身体心脏进行一系列生物力学测试，研究人类狭窄主动脉根部的弹性特性和微观结构；2)临床CT扫描的图像分析，将得到60个患者特定的主动脉瓣几何形状。将开发统计形状模型以便于重建过程以及描述患者群体中的解剖几何变化；以及3)主动脉组织-TAV结构相互作用和血流动力学的概率计算分析。确定性有限元(FE)模型和计算流体动力学(CFD)模型将使用TAV介入前测量的12名TAV患者的实际数据建立，并通过TAV后的临床CT扫描、流量和压力测量进行验证。患者材料特性和几何变化的统计描述将被映射到计算模型中，并将进行概率分析以评估主动脉组织-TAV结构相互作用和血流动力学。对TAV介入中涉及的生物力学的基础研究和组织-植入物相互作用的计算建模可能会导致一个新的知识库的发展，这是学术界、临床医生和心脏瓣膜行业以前无法获得的。这项研究中开发的方法和计算框架将作为未来研究的基础，其中将包括更多的设计和环境变量，如不同的患者人口统计数据，还可以用于促进针对不同瓣膜疾病(如二尖瓣返流)的其他新设备设计或术前患者筛查技术的开发。

DESCRIPTION (provided by applicant): Project Summary/Abstract Aortic stenosis is the most common valvular heart disease in the Western world and its prevalence is growing with an aging population. The current preferred method of treatment is complete valve replacement with a surgically implanted prosthetic valve. However, for high-risk patients with advanced age and co- morbidities, operative mortality escalates. Recently, minimally invasive transcatheter aortic valve (TAV) implantation has been investigated as an endovascular alternative to surgical valve replacement. Although significant experience has been gained, TAV implantation clinical trials have been associated with complications such as device migration, paravalvular leakage, coronary obstruction, and access site injury. Furthermore, the long-term durability and safety of TAV prostheses are largely unknown and must be evaluated and studied carefully. To gain a quantitative understanding of the biomechanics involved in TAV intervention, our objectives in this project are to develop probabilistic computational models to investigate aortic tissue-TAV structural interaction and hemodynamics under a variety of patient conditions, and to offer scientific rationale for TAV patient screening and TAV design improvement. To accomplish these goals, the following specific aims are proposed: 1) Investigation of elastic properties and microstructure of the human stenotic aortic root through a series of biomechanical tests performed on 50 human cadaver hearts; 2) Image analysis of clinical CT scans, which will yield 60 reconstructed patient-specific aortic valve geometries. Statistical shape models will be developed to facilitate the reconstruction process as well as the description of anatomic geometric variation among the patient population; and 3) Probabilistic computational analysis of aortic tissue-TAV structural interaction and hemodynamics. Deterministic finite element (FE) models and computational fluid dynamics (CFD) models will be developed using 12 actual TAV patient data measured prior to the TAV intervention, and validated by the post-TAV clinical CT scans, flow and pressure measurements. A statistical description of patient material properties and geometric variations will be mapped into the computational models and a probabilistic analysis will be conducted to evaluate aortic tissue-TAV structural interaction and hemodynamics. The fundamental study of the biomechanics involved in TAV intervention and the computational modeling of tissue-implant interaction proposed here could lead to the development of a new knowledgebase that has been previously unavailable to academia, clinicians, and the heart valve industry. The methodologies and computational framework developed in this study will serve as a basis for future studies, which will include more design and environmental variables such as different patient demographics, and could also be utilized to facilitate the development of other novel device designs or pre-operative patient screening techniques for different valve diseases, such as mitral valve regurgitation.