Institute for Computational Medicine and the Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA.
Institute of Biophysics and Institute of Physiology, Medical University of Graz, Graz, Austria.
Wiley Interdiscip Rev Syst Biol Med. 2010 Jul-Aug;2(4):489-506. doi: 10.1002/wsbm.76.
Computational approaches to investigating the electromechanics of healthy and diseased hearts are becoming essential for the comprehensive understanding of cardiac function. In this article, we first present a brief review of existing image-based computational models of cardiac structure. We then provide a detailed explanation of a processing pipeline which we have recently developed for constructing realistic computational models of the heart from high resolution structural and diffusion tensor (DT) magnetic resonance (MR) images acquired ex vivo. The presentation of the pipeline incorporates a review of the methodologies that can be used to reconstruct models of cardiac structure. In this pipeline, the structural image is segmented to reconstruct the ventricles, normal myocardium, and infarct. A finite element mesh is generated from the segmented structural image, and fiber orientations are assigned to the elements based on DTMR data. The methods were applied to construct seven different models of healthy and diseased hearts. These models contain millions of elements, with spatial resolutions in the order of hundreds of microns, providing unprecedented detail in the representation of cardiac structure for simulation studies.
计算方法在研究健康和患病心脏的机电特性方面变得至关重要，有助于全面理解心脏功能。本文首先简要回顾现有的基于图像的心脏结构计算模型。然后，我们详细介绍了最近开发的处理管道，用于从离体获取的高分辨率结构和扩散张量 (DT) 磁共振 (MR) 图像构建真实的心脏计算模型。该处理管道的介绍结合了可用于重建心脏结构模型的方法学回顾。在该管道中，对结构图像进行分割以重建心室、正常心肌和梗死区。从分割的结构图像生成有限元网格，并根据 DTMR 数据为元素分配纤维方向。该方法应用于构建七个不同的健康和患病心脏模型。这些模型包含数百万个元素，空间分辨率为数百微米量级，为心脏结构的模拟研究提供了前所未有的细节。
