Division of Medical Physics, University of Leeds, UK.
Phys Med Biol. 2011 Apr 21;56(8):2423-43. doi: 10.1088/0031-9155/56/8/007. Epub 2011 Mar 22.
Quantitative analysis of cardiac dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) perfusion datasets is dependent on the drawing (manually or automatically) of myocardial contours. The required accuracy of these contours for myocardial blood flow (MBF) estimation is not well understood. This study investigates the relationship between myocardial contour errors and MBF errors. Myocardial contours were manually drawn on DCE-MRI perfusion datasets of healthy volunteers imaged in systole. Systematic and random contour errors were simulated using spline curves and the resulting errors in MBF were calculated. The degree of contour error was also evaluated by two recognized segmentation metrics. We derived contour error tolerances in terms of the maximum deviation (MD) a contour could deviate radially from the 'true' contour expressed as a fraction of each volunteer's mean myocardial width (MW). Significant MBF errors were avoided by setting tolerances of MD ≤ 0.4 MW, when considering the whole myocardium, MD ≤ 0.3 MW, when considering six radial segments, and MD ≤ 0.2 MW for further subdivision into endo- and epicardial regions, with the exception of the anteroseptal region, which required greater accuracy. None of the considered segmentation metrics correlated with MBF error; thus, both segmentation metrics and MBF errors should be used to evaluate contouring algorithms.
心脏动态对比增强磁共振成像（DCE-MRI）灌注数据集的定量分析依赖于心肌轮廓的绘制（手动或自动）。这些轮廓对于心肌血流（MBF）估计的准确性要求尚不清楚。本研究探讨了心肌轮廓误差与 MBF 误差之间的关系。在收缩期对健康志愿者的 DCE-MRI 灌注数据集进行图像采集，手动绘制心肌轮廓。使用样条曲线模拟系统和随机轮廓误差，并计算由此产生的 MBF 误差。还使用两种公认的分割度量标准评估了轮廓误差的程度。我们根据轮廓相对于“真实”轮廓的最大径向偏差（MD）推导了轮廓误差容限，该偏差表示为每个志愿者平均心肌宽度（MW）的分数。当考虑整个心肌时，设定 MD≤0.4MW 的容限可以避免显著的 MBF 误差；当考虑六个径向段时，设定 MD≤0.3MW 的容限；进一步划分为心内膜和心外膜区域时，设定 MD≤0.2MW 的容限，除了前间隔区域需要更高的准确性。没有任何考虑的分割度量与 MBF 误差相关；因此，应同时使用分割度量和 MBF 误差来评估轮廓算法。
