Willerson Center for Cardiovascular Modeling and Simulation, Institute for Computational Engineering and Sciences, Department of Biomedical Engineering, The University of Texas at Austin, Austin, Texas.
Gorman Cardiovascular Research Group, Department of Surgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania.
Int J Numer Method Biomed Eng. 2018 Dec;34(12):e3142. doi: 10.1002/cnm.3142. Epub 2018 Sep 14.
Assessment of mitral valve (MV) function is important in many diagnostic, prognostic, and surgical planning applications for treatment of MV disease. Yet, to date, there are no accepted noninvasive methods for determination of MV leaflet deformation, which is a critical metric of MV function. In this study, we present a novel, completely noninvasive computational method to estimate MV leaflet in-plane strains from clinical-quality real-time three-dimensional echocardiography (rt-3DE) images. The images were first segmented to produce meshed medial-surface leaflet geometries of the open and closed states. To establish material point correspondence between the two states, an image-based morphing pipeline was implemented within a finite element (FE) modeling framework in which MV closure was simulated by pressurizing the open-state geometry, and local corrective loads were applied to enforce the actual MV closed shape. This resulted in a complete map of local systolic leaflet membrane strains, obtained from the final FE mesh configuration. To validate the method, we utilized an extant in vitro database of fiducially labeled MVs, imaged in conditions mimicking both the healthy and diseased states. Our method estimated local anisotropic in vivo strains with less than 10% error and proved to be robust to changes in boundary conditions similar to those observed in ischemic MV disease. Next, we applied our methodology to ovine MVs imaged in vivo with rt-3DE and compared our results to previously published findings of in vivo MV strains in the same type of animal as measured using surgically sutured fiducial marker arrays. In regions encompassed by fiducial markers, we found no significant differences in circumferential(P = 0.240) or radial (P = 0.808) strain estimates between the marker-based measurements and our novel noninvasive method. This method can thus be used for model validation as well as for studies of MV disease and repair.
评估二尖瓣(MV)功能对于 MV 疾病的治疗的许多诊断、预后和手术规划应用非常重要。然而,迄今为止,还没有被接受的无创方法来确定 MV 瓣叶的变形,这是 MV 功能的一个关键指标。在这项研究中,我们提出了一种新颖的、完全无创的计算方法,用于从临床质量的实时三维超声心动图(rt-3DE)图像中估计 MV 瓣叶的平面内应变。这些图像首先被分割,以产生开放和关闭状态的网格状中膜瓣叶几何形状。为了在两个状态之间建立质点对应关系,在有限元(FE)建模框架内实现了基于图像的变形管道,其中通过对开放状态的几何形状加压来模拟 MV 关闭,并且施加局部校正载荷以强制实际的 MV 关闭形状。这导致了从最终的 FE 网格配置中获得的局部收缩期瓣叶膜应变的完整图谱。为了验证该方法,我们利用现有的体外 MV 标记数据库,在模拟健康和疾病状态的条件下对其进行成像。我们的方法估计了局部各向异性的体内应变,误差小于 10%,并且对类似于缺血性 MV 疾病中观察到的边界条件变化具有鲁棒性。接下来,我们将我们的方法应用于在体 rt-3DE 成像的绵羊 MV,并将我们的结果与在同种动物中使用手术缝合的标记标记阵列测量的以前发表的 MV 应变的体内发现进行比较。在标记物包含的区域内,我们发现标记测量和我们的新无创方法之间的圆周(P=0.240)或径向(P=0.808)应变估计没有显著差异。因此,该方法可用于模型验证以及 MV 疾病和修复的研究。