Image Analytics and Medical Informatics, Siemens Corporate Research, Princeton, New Jersey 08540, USA.
Med Image Anal. 2012 Jul;16(5):1003-14. doi: 10.1016/j.media.2012.02.003. Epub 2012 Mar 1.
The cardiac valvular apparatus, composed of the aortic, mitral, pulmonary and tricuspid valves, is an essential part of the anatomical, functional and hemodynamic characteristics of the heart and the cardiovascular system as a whole. Valvular heart diseases often involve multiple dysfunctions and require joint assessment and therapy of the valves. In this paper, we propose a complete and modular patient-specific model of the cardiac valvular apparatus estimated from 4D cardiac CT data. A new constrained Multi-linear Shape Model (cMSM), conditioned by anatomical measurements, is introduced to represent the complex spatio-temporal variation of the heart valves. The cMSM is exploited within a learning-based framework to efficiently estimate the patient-specific valve parameters from cine images. Experiments on 64 4D cardiac CT studies demonstrate the performance and clinical potential of the proposed method. Our method enables automatic quantitative evaluation of the complete valvular apparatus based on non-invasive imaging techniques. In conjunction with existent patient-specific chamber models, the presented valvular model enables personalized computation modeling and realistic simulation of the entire cardiac system.
心脏瓣膜装置由主动脉瓣、二尖瓣、肺动脉瓣和三尖瓣组成，是心脏和整个心血管系统解剖学、功能和血液动力学特征的重要组成部分。瓣膜性心脏病常涉及多种功能障碍，需要联合评估和治疗瓣膜。本文提出了一种基于 4D 心脏 CT 数据的完整的、模块化的心脏瓣膜患者特定模型。引入了一种新的受解剖学测量条件约束的多线性形状模型(cMSM)，以表示心脏瓣膜的复杂时空变化。cMSM 被应用于基于学习的框架中，从电影图像中有效地估计患者特定的瓣膜参数。对 64 项 4D 心脏 CT 研究的实验证明了该方法的性能和临床潜力。我们的方法可以基于非侵入性成像技术自动对整个瓣膜装置进行定量评估。与现有的患者特定心室模型结合，所提出的瓣膜模型可以实现整个心脏系统的个性化计算建模和真实模拟。
