van Geuns Robert Jan M, Baks Timo, Gronenschild Ed H B M, Aben Jean-Paul M M, Wielopolski Piotr A, Cademartiri Filippo, de Feyter Pim J
Department of Cardiology, Erasmus Medical Center, Thoraxcenter Ba 585, PO Box 2040, 3000 CA Rotterdam, The Netherlands.
Radiology. 2006 Jul;240(1):215-21. doi: 10.1148/radiol.2401050471.
The purpose of this study was to evaluate an automatic boundary detection algorithm of the left ventricle on magnetic resonance (MR) short-axis images with the essential restriction of no manual corrections. The study comprised 13 patients (nine men, four women) and 12 healthy volunteers (11 men, one woman), and institutional review board approval and informed consent were obtained. The outline of the left ventricle was indicated manually on horizontal and vertical long-axis MR images. The calculated intersection points with the short-axis MR images were the basis of the automatic contour detection. Automatically derived volumes correlated highly with manually derived (short axis-based) volumes (R2 = 0.98); ejection fraction (EF) and mass showed a correlation of 0.95 and 0.93, respectively. Automatic contour detection reduced interobserver variability to 0.1 mL for endocardial end-diastolic and end-systolic volumes, 1.1 mL for epicardial end-diastolic and end-systolic volumes, 0.02% for EF, and 1.1 g for mass. Thus, the algorithm enabled highly reproducible left ventricular parameters to be obtained.
本研究的目的是评估一种用于磁共振（MR）短轴图像上左心室的自动边界检测算法，其基本限制是无需人工校正。该研究纳入了13例患者（9名男性，4名女性）和12名健康志愿者（11名男性，1名女性），并获得了机构审查委员会的批准和知情同意。在水平和垂直长轴MR图像上手动勾勒出左心室的轮廓。与短轴MR图像计算得出的交点是自动轮廓检测的基础。自动得出的容积与手动得出的（基于短轴的）容积高度相关（R2 = 0.98）；射血分数（EF）和质量的相关性分别为0.95和0.93。自动轮廓检测将观察者间的心内膜舒张末期和收缩末期容积的变异性降低至0.1 mL，心包膜舒张末期和收缩末期容积的变异性降低至1.1 mL，EF的变异性降低至0.02%，质量的变异性降低至1.1 g。因此，该算法能够获得高度可重复的左心室参数。
