Probabilistic Modeling of Stenotic Aortic Valve Intervention

描述（由申请人提供）：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病，其患病率随着人口老龄化而增长。目前首选的治疗方法是用手术植入的人工瓣膜进行完全瓣膜置换。然而，对于高龄和合并症的高风险患者，手术死亡率上升。最近，微创经导管主动脉瓣（TAV）植入已被研究作为外科瓣膜置换术的血管内替代方法。尽管已经获得了大量经验，但TAV植入临床试验与器械移位、瓣周漏、冠状动脉阻塞和穿刺部位损伤等并发症相关。此外，TAV假体的长期耐久性和安全性在很大程度上是未知的，必须仔细评估和研究。为了定量了解TAV介入中涉及的生物力学，本项目的目标是开发概率计算模型，以研究各种患者条件下主动脉组织-TAV结构相互作用和血液动力学，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例人尸体心脏进行的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，这将产生60个重建的患者特定的主动脉瓣几何形状。将开发统计形状模型，以促进重建过程以及描述患者人群中的解剖几何变化;和3）主动脉组织-TAV结构相互作用和血液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例实际TAV患者数据开发，并通过TAV后临床CT扫描、流量和压力测量进行确认。将患者材料特性和几何变化的统计描述映射到计算模型中，并进行概率分析，以评价主动脉组织-TAV结构相互作用和血液动力学。TAV介入中涉及的生物力学的基础研究和本文提出的组织-植入物相互作用的计算建模可能会导致学术界、临床医生和心脏瓣膜行业以前无法获得的新知识库的开发。本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学，也可用于促进开发其他新型器械设计或不同瓣膜疾病的术前患者筛选技术，如二尖瓣返流。

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.