Zhang Xingyu, Medrano-Gracia Pau, Ambale-Venkatesh Bharath, Bluemke David A, Cowan Brett R, Finn J Paul, Kadish Alan H, Lee Daniel C, Lima Joao A C, Young Alistair A, Suinesiaputra Avan
Department of Anatomy and Medical Imaging, University of Auckland, Auckland, New Zealand.
The Donald W. Reynolds Cardiovascular Clinical Research Center, The Johns Hopkins University, Baltimore, USA.
Gigascience. 2017 Mar 1;6(3):1-15. doi: 10.1093/gigascience/gix005.
Left ventricular size and shape are important for quantifying cardiac remodeling in response to cardiovascular disease. Geometric remodeling indices have been shown to have prognostic value in predicting adverse events in the clinical literature, but these often describe interrelated shape changes. We developed a novel method for deriving orthogonal remodeling components directly from any (moderately independent) set of clinical remodeling indices.
Six clinical remodeling indices (end-diastolic volume index, sphericity, relative wall thickness, ejection fraction, apical conicity, and longitudinal shortening) were evaluated using cardiac magnetic resonance images of 300 patients with myocardial infarction, and 1991 asymptomatic subjects, obtained from the Cardiac Atlas Project. Partial least squares (PLS) regression of left ventricular shape models resulted in remodeling components that were optimally associated with each remodeling index. A Gram-Schmidt orthogonalization process, by which remodeling components were successively removed from the shape space in the order of shape variance explained, resulted in a set of orthonormal remodeling components. Remodeling scores could then be calculated that quantify the amount of each remodeling component present in each case. A one-factor PLS regression led to more decoupling between scores from the different remodeling components across the entire cohort, and zero correlation between clinical indices and subsequent scores.
The PLS orthogonal remodeling components had similar power to describe differences between myocardial infarction patients and asymptomatic subjects as principal component analysis, but were better associated with well-understood clinical indices of cardiac remodeling. The data and analyses are available from www.cardiacatlas.org.
左心室的大小和形状对于量化心血管疾病所致的心脏重塑至关重要。在临床文献中，几何重塑指数已被证明在预测不良事件方面具有预后价值，但这些指数往往描述的是相互关联的形状变化。我们开发了一种新方法，可直接从任何一组（适度独立的）临床重塑指数中得出正交重塑成分。
使用从心脏图谱项目获取的300例心肌梗死患者和1991例无症状受试者的心脏磁共振图像，对六个临床重塑指数（舒张末期容积指数、球形度、相对壁厚、射血分数、心尖锥度和纵向缩短）进行了评估。左心室形状模型的偏最小二乘（PLS）回归产生了与每个重塑指数最佳相关的重塑成分。通过Gram-Schmidt正交化过程，按照形状方差解释的顺序从形状空间中依次去除重塑成分，得到了一组正交归一化的重塑成分。然后可以计算重塑分数，以量化每种情况下存在的每种重塑成分的量。单因素PLS回归导致整个队列中不同重塑成分的分数之间的解耦更多，并且临床指数与后续分数之间的相关性为零。
PLS正交重塑成分在描述心肌梗死患者和无症状受试者之间的差异方面具有与主成分分析相似的能力，但与已充分理解的心脏重塑临床指数的相关性更好。数据和分析可从www.cardiacatlas.org获取。
