Zhang Xingyu, Cowan Brett R, Bluemke David A, Finn J Paul, Fonseca Carissa G, Kadish Alan H, Lee Daniel C, Lima Joao A C, Suinesiaputra Avan, Young Alistair A, Medrano-Gracia Pau
Department of Anatomy with Radiology, University of Auckland, Auckland, New Zealand.
National Institute of Biomedical Imaging and Bioengineering, Bethesda, Maryland, United States of America.
PLoS One. 2014 Oct 31;9(10):e110243. doi: 10.1371/journal.pone.0110243. eCollection 2014.
Myocardial infarction leads to changes in the geometry (remodeling) of the left ventricle (LV) of the heart. The degree and type of remodeling provides important diagnostic information for the therapeutic management of ischemic heart disease. In this paper, we present a novel analysis framework for characterizing remodeling after myocardial infarction, using LV shape descriptors derived from atlas-based shape models. Cardiac magnetic resonance images from 300 patients with myocardial infarction and 1991 asymptomatic volunteers were obtained from the Cardiac Atlas Project. Finite element models were customized to the spatio-temporal shape and function of each case using guide-point modeling. Principal component analysis was applied to the shape models to derive modes of shape variation across all cases. A logistic regression analysis was performed to determine the modes of shape variation most associated with myocardial infarction. Goodness of fit results obtained from end-diastolic and end-systolic shapes were compared against the traditional clinical indices of remodeling: end-diastolic volume, end-systolic volume and LV mass. The combination of end-diastolic and end-systolic shape parameter analysis achieved the lowest deviance, Akaike information criterion and Bayesian information criterion, and the highest area under the receiver operating characteristic curve. Therefore, our framework quantitatively characterized remodeling features associated with myocardial infarction, better than current measures. These features enable quantification of the amount of remodeling, the progression of disease over time, and the effect of treatments designed to reverse remodeling effects.
心肌梗死会导致心脏左心室（LV）的几何形状发生变化（重塑）。重塑的程度和类型为缺血性心脏病的治疗管理提供了重要的诊断信息。在本文中，我们提出了一种新颖的分析框架，用于表征心肌梗死后的重塑情况，该框架使用从基于图谱的形状模型中导出的左心室形状描述符。来自心脏图谱项目的300例心肌梗死患者和1991名无症状志愿者的心脏磁共振图像被获取。使用引导点建模为每个病例的时空形状和功能定制有限元模型。对形状模型应用主成分分析，以得出所有病例中形状变化的模式。进行逻辑回归分析，以确定与心肌梗死最相关的形状变化模式。将从舒张末期和收缩末期形状获得的拟合优度结果与传统的重塑临床指标进行比较：舒张末期容积、收缩末期容积和左心室质量。舒张末期和收缩末期形状参数分析的组合实现了最低的偏差、赤池信息准则和贝叶斯信息准则，以及最高的受试者工作特征曲线下面积。因此，我们的框架比当前的测量方法更能定量地表征与心肌梗死相关的重塑特征。这些特征能够对重塑量、疾病随时间的进展以及旨在逆转重塑效应的治疗效果进行量化。
