Sacks Michael, Drach Andrew, Lee Chung-Hao, Khalighi Amir, Rego Bruno, Zhang Will, Ayoub Salma, Yoganathan Ajit, Gorman Robert C, Gorman Iii Joseph H
aWillerson Center for Cardiovascular Modeling and Simulation, Institute for Computational Engineering and Sciences and the Department of Biomedical Engineering, The University of Texas at Austin, Austin, TX.
Willerson Center for Cardiovascular Modeling and Simulation, Institute for Computational Engineering and Sciences and the Department of Biomedical Engineering, The University of Texas at Austin, Austin, TX.
J Biomech Eng. 2019 Apr 20;141(7):0708041-07080422. doi: 10.1115/1.4043552.
The mitral valve (MV) is the heart valve that regulates blood ?ow between the left atrium and left ventricle (LV). In situations where the MV fails to fully cover the left atrioventricular ori?ce during systole, the resulting regurgitation causes pulmonary congestion, leading to heart failure and/or stroke. The causes of MV insuf?ciency can be either primary (e.g. myxomatous degeneration) where the valvular tissue is organically diseased, or secondary (typically inducded by ischemic cardiomyopathy) termed ischemic mitral regurgitation (IMR), is brought on by adverse LV remodeling. IMR is present in up to 40% of patients and more than doubles the probability of cardiovascular morbidity after 3.5 years. There is now agreement that adjunctive procedures are required to treat IMR caused by lea?et tethering. However, there is no consensus regarding the best procedure. Multicenter registries and randomized trials would be necessary to prove which procedure is superior. Given the number of proposed procedures and the complexity and duration of such studies, it is highly unlikely that IMR procedure optimization will be achieved by prospective clinical trials. There is thus an urgent need for cell and tissue physiologically based quantitative assessments of MV function to better design surgical solutions and associated therapies. Novel computational approaches directed towards optimized surgical repair procedures can substantially reduce the need for such trial-and-error approaches. We present the details of our MV modeling techniques, with an emphasis on what is known and investigated at various length scales.
二尖瓣（MV）是调节左心房和左心室（LV）之间血流的心脏瓣膜。在收缩期二尖瓣无法完全覆盖左房室口的情况下，由此产生的反流会导致肺充血，进而导致心力衰竭和/或中风。二尖瓣关闭不全的原因可以是原发性的（如黏液瘤样变性），即瓣膜组织发生器质性病变，也可以是继发性的（通常由缺血性心肌病引起），称为缺血性二尖瓣反流（IMR），由左心室不良重塑引起。IMR在高达40%的患者中存在，并且使3.5年后心血管疾病发病的可能性增加一倍以上。目前人们一致认为，需要辅助手术来治疗由瓣叶牵拉引起的IMR。然而，对于最佳手术方法尚无共识。需要多中心登记研究和随机试验来证明哪种手术方法更优。鉴于所提出的手术方法数量以及此类研究的复杂性和持续时间，通过前瞻性临床试验实现IMR手术优化的可能性极小。因此，迫切需要基于细胞和组织生理学的二尖瓣功能定量评估，以更好地设计手术解决方案和相关治疗方法。针对优化手术修复程序的新型计算方法可以大幅减少这种试错方法的需求。我们介绍了我们的二尖瓣建模技术细节，重点是在不同长度尺度上已知和研究的内容。
