Estimation of left ventricular cavity area with an on-line, semiautomated echocardiographic edge detection system.
Estimation of left ventricular cavity area with an on-line, semiautomated echocardiographic edge detection system.
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使用在线、半自动超声心动图边缘检测系统估计左心室腔面积。
DOI：
10.1161/01.cir.86.1.159
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发表时间：
1992
期刊：
影响因子：
37.8
通讯作者：
Skorton,DJ
中科院分区：
文献类型：
--
作者：
Vandenberg,BF;Rath,LS;Stuhlmuller,P;MeltonJr,HE;Skorton,DJ
背景技术超声心动图中心内膜边界的自动边缘检测提供了对空腔面积的客观、可重复的估计；然而，大多数方法都需要离线分析。最近开发的原型超声心动图成像系统允许在成像过程中进行实时自动边缘检测，因此具有测量腔面积周期性变化和在线评估左心室功能的潜力。我们的目的是将传统超声心动图手动追踪的心内膜面积测量值与正常受试者的实时自动边缘检测系统获得的测量值进行比较。方法和结果使用两个训练图像集来建立增益设置的最佳方法；然后在一组测试图像中评估这些设置。在高增益训练组（n = 8 名受试者，119 张图像）中，增益设置调整得足够高，以显示至少 90% 的心内膜边界。手动绘制和实时面积测量的相关性为 r = 0.92，但计算机低估了手动绘制的面积。在低增益训练组（n = 7 名受试者，104 幅图像）中，增益设置调整得足够低，以避免腔内混乱，尽管存在心内膜边缘丢失。手动绘制的区域和实时区域再次相关（r = 0.79），但手动绘制的区域被计算机高估了。在中间增益测试组（n = 7 名受试者，105 个图像）中，增益设置在最大心内膜清晰度（大于或等于 90%）和最小腔杂波（小于或等于 1 cm2）之间进行平衡。组中手动绘制的区域和实时区域的相关性为 r = 0.91，个体受试者的 r 范围为 0.94 至 0.99。手动追踪区域的观察者间变异性为 9.5%，实时区域测量的观察者间变异性为 10.6%。结论实时在线自动边缘检测可准确估计手动绘制的空腔区域。尽管该方法依赖于增益，但测量结果是可重复的。该系统应该在左心室功能测量很重要的环境中具有临床应用。
BACKGROUNDAutomated edge detection of endocardial borders in echocardiograms provides objective, reproducible estimation of cavity area; however, most methods have required off-line analysis. A recently developed prototype echocardiographic imaging system permits real-time automated edge detection during imaging and thus, the potential for measurement of cyclic changes in cavity area and the assessment of left ventricular function on-line. Our purpose was to compare measurements of endocardial area manually traced from conventional echocardiograms with those obtained with the real-time automated edge detection system in normal subjects.METHODS AND RESULTSTwo training sets of images were used to establish optimal methods of gain setting; the settings were then evaluated in a test set of images. In the high-gain training group (n = 8 subjects, 119 images), gain settings were adjusted sufficiently high to display at least 90% of the endocardial border. Manually drawn and real-time area measurements correlated at r = 0.92, but manually drawn areas were underestimated by computer. In the low-gain training group (n = 7 subjects, 104 images), gain settings were adjusted sufficiently low to avoid cavity clutter despite the presence of dropout of endocardial edges. Manually drawn and real-time areas again correlated (r = 0.79), but manually drawn areas were overestimated by computer. In the intermediate-gain test group (n = 7 subjects, 105 images), gain settings were balanced between maximal endocardial definition (greater than or equal to 90%) and minimal cavity clutter (less than or equal to 1 cm2). Manually drawn and real-time areas correlated at r = 0.91 for the group, and r ranged from 0.94 to 0.99 in individual subjects. Interobserver variability was 9.5% for manually traced areas and 10.6% for real-time area measurements.CONCLUSIONSReal-time on-line automated edge detection provides accurate estimation of manually drawn cavity areas. Although the method is gain dependent, measurements are reproducible. The system should have clinical application in settings in which measurements of left ventricular function are important.
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影响因子：
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作者：
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DOI：
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期刊：
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