Dynamic assessment of cardiac functions by means of cardiac ultrasound elastography

心血管疾病的早期检测一直是医学影像学中非常活跃和重要的研究领域。特别是，有证据表明，许多严重的心脏疾病可以成功地确定通过表征的区域心脏功能。由于这个原因，心脏弹性成像作为一种相对较新的和非常有前途的技术，用于分析和可视化的局部和整体的心脏的机械功能，有越来越多的兴趣，不幸的是，心脏弹性成像目前的进展似乎已经受到阻碍的缺乏真正的方法来估计局部应变（和/或其速率）的心肌。现有的估计方法不能提供可靠结果的主要原因是：1）用于增强心脏图像的工具的非最优性和2）用于描述活体心脏动力学的模型的非最优性。该项目的目标包括：1）开发计算效率高、鲁棒性强、准确的心脏图像增强预处理算法;2）开发有效可靠的心脏图像预处理序列心脏动力学估计方法;3）建立自动区分心肌正常和异常区域的最相关标准; 4）通过模拟、基于模型的实验和体内研究探索心脏弹性成像在检测缺血和梗死中的作用。5）开发用于在商业扫描仪上实施该方法的程序包。

Early detection of cardiovascular diseases has long become a very active and important research area in medical imaging. In particular, there exists evidence that many critical cardiac disorders can be successfully determined through characterization of the regional cardiac function. For this reason, there has been ever increasing interest in cardiac elastography as a relatively new and very promising technique for analyzing and visualizing the local and global mechanical functions of the heart.Unfortunately, the current progress of cardiac elastography seems to have been hampered by the absence of bona fide methods for estimating the local strains (and/or their rates) of the cardiac muscle. Among the main reasons for which the existing estimation methods fall short to provide reliable results are: 1) non-optimality of the tools used for enhancing the cardiac images and 2) non-optimality of the models used to describe the dynamics of a living heart.The proposed research program is aimed at developing a qualitatively new system for cardiac elastography. The objectives of the program include:1) Development of computationally efficient, robust and accurate preprocessing algorithms for enhancement of cardiac images;2) Development of efficient and reliable methods for estimating the cardiac dynamics from the preprocessed sequences of cardiac images;3) Establishment of the most relevant criteria for automatic discrimination between normal and abnormal regions of the cardiac muscle;4) Exploration of the role of cardiac elastography in the detection of ischemia and infarction via simulations, phantom-based experiments and in vivo study.5) Development of a package of procedures for implementing the method on commercial scanners.