首页> 外文期刊>Annals of Biomedical Engineering: The Journal of the Biomedical Engineering Society >Computational method for identifying and quantifying shape features of human left ventricular remodeling.
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Computational method for identifying and quantifying shape features of human left ventricular remodeling.

机译:用于识别和量化人体左心室重构的形状特征的计算方法。

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Left ventricular remodeling during the development of heart failure is a strong predictor of cardiovascular mortality. However, methods to objectively quantify remodeling-associated shape changes are not routinely available but may be possible with new computational anatomy tools. In this study, we analyzed and compared multi-detector computed tomographic (MDCT) images of ventricular shape at end-systole (ES) and end-diastole (ED) to determine whether regional structural characteristics could be identified and, as a proof of principle, whether differences in hearts of patients with anterior myocardial infarction (MI) and ischemic cardiomyopathy (ICM) could be distinguished from those with global nonischemic cardiomyopathy (NICM). MDCT images of hearts from 11 patients (5 with ICM) with ejection fractions (EF) < 35% were analyzed. An average ventricular shape model (template) was constructed for each cardiac phase by bringing heart shapes into correspondence using linear and nonlinear image matching algorithms. Next, transformation fields were computed between the template image and individual heart images in the population. Principal component analysis (PCA) method was used to quantify ventricular shape differences described by the transformation vector fields. Statistical analysis of PCA coefficients revealed significant ventricular shape differences at ED (p = 0.03) and ES (p = 0.03). For validation, a second set of 14 EF-matched patients (8 with ICM) were evaluated. The discrimination rule learned from the training data set was able to differentiate ICM from NICM patients (p = 0.008). Application of a novel shape analysis method to in vivo human cardiac images acquired on a clinical scanner is feasible and can quantify regional shape differences at end-systole in remodeled myopathic human myocardium. This approach may be useful in identifying differences in the remodeling process between ICM and NICM populations and possibly in differentiating the populations.
机译:心力衰竭发展过程中的左心室重塑是心血管疾病死亡率的重要预测指标。但是,通常无法获得客观量化与重塑相关的形状变化的方法,但是使用新的计算解剖学工具可能是可行的。在这项研究中,我们分析并比较了心脏收缩末期(ES)和心脏舒张末期(ED)的心室形状的多探测器计算机断层扫描(MDCT)图像,以确定是否可以识别区域结构特征,并作为原理证明,是否可以将有前瞻性心肌梗死(MI)和缺血性心肌病(ICM)的患者的心脏区别与具有整体性非缺血性心肌病(NICM)的患者进行区分。分析了11例射血分数(EF)<35%的患者(5例ICM)心脏的MDCT图像。通过使用线性和非线性图像匹配算法将心脏形状对应起来,为每个心脏阶段构建了平均心室形状模型(模板)。接下来,在模板图像和总体中的单个心脏图像之间计算转换场。主成分分析(PCA)方法用于量化由转换向量场描述的心室形状差异。 PCA系数的统计分析显示,在ED(p = 0.03)和ES(p = 0.03)时,心室形状存在显着差异。为了进行验证,评估了另一组14名EF匹配患者(其中8名患有ICM)。从训练数据集中学习到的区分规则能够将ICM与NICM患者区分开(p = 0.008)。一种新颖的形状分析方法在临床扫描仪上获取的体内人心脏图像中的应用是可行的,并且可以在重塑的肌病性人心肌的收缩末期量化区域形状差异。该方法可能有助于识别ICM和NICM人群之间在重塑过程中的差异,并可能有助于区分人群。

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