Non-invasive Cardiology Unit, Hillel-Yaffe Medical Center, Hadera, Israel.
Eur Heart J Cardiovasc Imaging. 2012 Mar;13(3):257-62. doi: 10.1093/ejechocard/jer182. Epub 2011 Nov 6.
Assessing the quality of wall motion (WM) on echocardiograms remains a challenge. Previously, we validated an automated application used by experienced echocardiographers for WM classification based on longitudinal two-dimensional (2D) strain. The aim of this study was to show that the use of this automatic application was independent of the user's experience.
We compared the WM classifications obtained by the application when used by 12 highly experienced readers (Exp-R) vs. 11 inexperienced readers (InExp-R). Both classifications were compared with expert consensus classifications using the standard visual method. Digitized clips of cardiac cycles from three apical views in 105 patients were used for these analyses. Reproducibility of both groups was high (overall intra-class correlation coefficient: InExp-R = 0.89, Exp-R = 0.83); the lowest was noted for hypokinetic segments (InExp-R = 0.79, Exp-R = 0.72). InExp-R scores were concordant with Exp-R mode scores in 88.8% of segments; they were overestimated in 5.8% and underestimated in 3.2%. The sensitivity, specificity, and accuracy of InExp-R vs. Exp-R for classifying segments as normal/abnormal were identical (87, 85, and 86%, respectively).
Classification of WM from apical views with an automatic application based on longitudinal 2D strain by InExp-R vs. Exp-R was similar to visual classification by Exp-R. This application may be useful for inexperienced echocardiographers/technicians and may serve as an automated 'second opinion' for experienced echocardiographers.
评估超声心动图的心肌运动质量仍然具有挑战性。此前,我们验证了一种基于纵向二维(2D)应变的自动应用程序,该应用程序由经验丰富的超声心动图医师用于心肌运动分类。本研究旨在表明该自动应用程序的使用与用户的经验无关。
我们比较了该应用程序在 12 名经验丰富的读者(Exp-R)和 11 名无经验读者(InExp-R)使用时的心肌运动分类。使用标准的视觉方法将两种分类与专家共识分类进行比较。这些分析使用了来自 105 例患者三个心尖视图的心脏周期的数字化剪辑。两组的再现性均较高(总体组内相关系数:InExp-R=0.89,Exp-R=0.83);最低的是运动减弱节段(InExp-R=0.79,Exp-R=0.72)。InExp-R 评分与 Exp-R 模式评分在 88.8%的节段中一致;在 5.8%的节段中高估,在 3.2%的节段中低估。InExp-R 与 Exp-R 相比,用于将节段分类为正常/异常的敏感性、特异性和准确性相同(分别为 87%、85%和 86%)。
由经验丰富的超声心动图医师使用自动应用程序基于纵向 2D 应变对心尖视图的心肌运动进行分类与经验丰富的超声心动图医师的视觉分类相似。该应用程序可用于无经验的超声心动图医师/技师,也可作为经验丰富的超声心动图医师的自动“第二意见”。