基于运动对称分析的生物人工心脏瓣膜耐久性评估

M. Alizadeh, Melissa Cote, A. Albu
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摘要

本文通过基于计算机视觉(CV)的瓣膜叶运动视觉对称性分析,研究了生物人工心脏瓣膜(BHV)的耐久性估计。bhv通常被植入患有瓣膜性心脏病的患者。阀门设计经过了心血管设备的严格测试,但一旦植入,超过50%的bhv会在15年内出现结构故障。我们研究了BHV小叶的视觉动态对称性与瓣膜功能对称性之间的相关性。我们假设阀瓣运动的不对称会产生流动模式的不对称,导致部分阀瓣上的局部应力和力增加,从而加速阀瓣的失效。我们提出了基于正交投影矩阵对角线(DOPM)和动态时间规整(DTW)的两种不同的成对小叶对称分数,从脉动流测试期间记录的视频中计算得到。我们比较了对称分数分布与那些流体动力学参数(速度和涡量值)在小叶边界,从阀门特定的数值模拟获得。在包括三种不同三尖瓣bhv的四种情况下进行的实验取得了令人满意的结果,DTW分数与模拟结果显示出良好的一致性。通过建立视觉对称性和功能对称性之间的联系,该方法为使用CV技术进行BHV耐久性评估铺平了道路。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Towards Durability Estimation of Bioprosthetic Heart Valves Via Motion Symmetry Analysis
This paper addresses bioprosthetic heart valve (BHV) durability estimation via computer vision (CV)-based analyses of the visual symmetry of valve leaflet motion. BHVs are routinely implanted in patients suffering from valvular heart diseases. Valve designs are rigorously tested using cardiovascular equipment, but once implanted, more than 50% of BHVs encounter a structural failure within 15 years. We investigate the correlation between the visual dynamic symmetry of BHV leaflets and the functional symmetry of the valves. We hypothesize that an asymmetry in the valve leaflet motion will generate an asymmetry in the flow patterns, resulting in added local stress and forces on some of the leaflets, which can accelerate the failure of the valve. We propose two different pair-wise leaflet symmetry scores based on the diagonals of orthogonal projection matrices (DOPM) and on dynamic time warping (DTW), computed from videos recorded during pulsatile flow tests. We compare the symmetry score profiles with those of fluid dynamic parameters (velocity and vorticity values) at the leaflet borders, obtained from valve-specific numerical simulations. Experiments on four cases that include three different tricuspid BHVs yielded promising results, with the DTW scores showing a good coherence with respect to the simulations. With a link between visual and functional symmetries established, this approach paves the way towards BHV durability estimation using CV techniques.
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