Glasgow Computational Engineering Centre, James Watt School of Engineering, University of Glasgow, Glasgow, G12 8LT, Scotland, United Kingdom.
Department of Radiology, University of Pennsylvania, Philadelphia, PA, USA.
Med Image Anal. 2023 Jul;87:102804. doi: 10.1016/j.media.2023.102804. Epub 2023 Apr 1.
Even though the central role of mechanics in the cardiovascular system is widely recognized, estimating mechanical deformation and strains in-vivo remains an ongoing practical challenge. Herein, we present a semi-automated framework to estimate strains from four-dimensional (4D) echocardiographic images and apply it to the aortic roots of patients with normal trileaflet aortic valves (TAV) and congenital bicuspid aortic valves (BAV). The method is based on fully nonlinear shell-based kinematics, which divides the strains into in-plane (shear and dilatational) and out-of-plane components. The results indicate that, even for size-matched non-aneurysmal aortic roots, BAV patients experience larger regional shear strains in their aortic roots. This elevated strains might be a contributing factor to the higher risk of aneurysm development in BAV patients. The proposed framework is openly available and applicable to any tubular structures.
尽管力学在心血管系统中的核心作用已被广泛认可,但在体内估计力学变形和应变仍然是一个持续存在的实际挑战。在此,我们提出了一种半自动框架,用于从四维(4D)超声心动图图像中估计应变,并将其应用于三叶式正常主动脉瓣(TAV)和先天性二叶式主动脉瓣(BAV)患者的主动脉根部。该方法基于全非线性壳基运动学,将应变分为平面内(剪切和膨胀)和平面外分量。结果表明,即使对于大小匹配的非动脉瘤性主动脉根部,BAV 患者的主动脉根部也会经历更大的局部剪切应变。这种增加的应变可能是 BAV 患者动脉瘤发展风险更高的一个因素。所提出的框架是公开可用的,适用于任何管状结构。