Auckland Bioengineering Institute, University of Auckland, Auckland, New Zealand.
Biomedical Image Analysis Group, Department of Computing, Imperial College London, London, UK.
Sci Rep. 2019 Feb 4;9(1):1130. doi: 10.1038/s41598-018-37916-6.
Left ventricular (LV) mass and volume are important indicators of clinical and pre-clinical disease processes. However, much of the shape information present in modern imaging examinations is currently ignored. Morphometric atlases enable precise quantification of shape and function, but there has been no objective comparison of different atlases in the same cohort. We compared two independent LV atlases using MRI scans of 4547 UK Biobank participants: (i) a volume atlas derived by automatic non-rigid registration of image volumes to a common template, and (ii) a surface atlas derived from manually drawn epicardial and endocardial surface contours. The strength of associations between atlas principal components and cardiovascular risk factors (smoking, diabetes, high blood pressure, high cholesterol and angina) were quantified with logistic regression models and five-fold cross validation, using area under the ROC curve (AUC) and Akaike Information Criterion (AIC) metrics. Both atlases exhibited similar principal components, showed similar relationships with risk factors, and had stronger associations (higher AUC and lower AIC) than a reference model based on LV mass and volume, for all risk factors (DeLong p < 0.05). Morphometric variations associated with each risk factor could be quantified and visualized and were similar between atlases. UK Biobank LV shape atlases are robust to construction method and show stronger relationships with cardiovascular risk factors than mass and volume.
左心室（LV）质量和容量是临床和临床前疾病过程的重要指标。然而，目前现代影像学检查中存在的大量形状信息都被忽略了。形态计量学图谱可实现对形状和功能的精确量化，但目前还没有在同一队列中对不同图谱进行客观比较的研究。我们使用 4547 名英国生物库参与者的 MRI 扫描对两种独立的 LV 图谱进行了比较：（i）通过对图像体积到公共模板的自动非刚性配准得出的体积图谱，以及（ii）从手动绘制的心外膜和心内膜表面轮廓得出的表面图谱。使用逻辑回归模型和五重交叉验证，通过 ROC 曲线下面积（AUC）和赤池信息量准则（AIC）指标，对图谱主成分与心血管危险因素（吸烟、糖尿病、高血压、高胆固醇和心绞痛）之间的关联强度进行了量化。两种图谱都表现出相似的主成分，与危险因素具有相似的关系，并且与基于 LV 质量和体积的参考模型相比，与所有危险因素（DeLong p < 0.05）的关联更强（AUC 更高，AIC 更低）。可以对与每个危险因素相关的形态变化进行量化和可视化，并且在两种图谱之间是相似的。英国生物库 LV 形状图谱对构建方法具有鲁棒性，并且与心血管危险因素的相关性强于质量和体积。
