Institut de Recherches Cliniques de Montreal, University of Montreal, Montreal, Quebec, Canada.
Ultrasound Med Biol. 2010 Sep;36(9):1513-24. doi: 10.1016/j.ultrasmedbio.2010.05.021.
Intra- and interobserver variability in Doppler echocardiographic velocity measurements (DEVM) is a significant issue. Indeed, imprecisions of DEVM can lead to diagnostic errors, particularly in the quantification of the severity of heart valve dysfunctions. To reduce the variability and rapidity of DEVM, we have developed an automatic method of Doppler velocity wave contour detection, based on active contour models. To validate our new method, results obtained with this method were compared with those obtained manually by two experienced echocardiographers on Doppler echocardiographic images of left ventricular outflow tract and transvalvular flow velocity signals recorded in 30 patients with aortic or mitral stenosis, 20 with normal sinus rhythm and 10 with atrial fibrillation. We focused on the three essential variables that are measured routinely using Doppler echocardiography in the clinical setting: the maximum velocity (Vmax), the mean velocity (Vmean) and the velocity-time integral (VTI). Comparison between the two methods has shown a very good agreement. A small bias value was found between the two methods (between -3.9% and 0.5% for Vmax, between -4.6% and -1.4% for Vmean and between -3.6% and 4.4% for VTI). Moreover, the computation time was short, approximately 5 s. This new method applied to DEVM could, therefore, provide a useful tool to eliminate the intra- and interobserver variabilities associated with DEVM and thereby to improve the accuracy of the diagnosis of cardiovascular disease. This automatic method could also allow the echocardiographer to realize these measurements within a much shorter period of time compared with the standard manual tracing method. From a practical point of view, the model developed can be easily implemented in a standard echocardiographic system.
多普勒超声心动图速度测量（DEVM）的观察者内和观察者间变异性是一个重要问题。事实上，DEVM 的不精确性可能导致诊断错误，尤其是在心脏瓣膜功能障碍严重程度的定量方面。为了减少 DEVM 的变异性和速度，我们开发了一种基于主动轮廓模型的多普勒速度波轮廓自动检测方法。为了验证我们的新方法，将该方法获得的结果与两位有经验的超声心动图医师手动获得的结果进行了比较，这些结果来自 30 例主动脉瓣或二尖瓣狭窄、20 例窦性心律正常和 10 例心房颤动患者的左心室流出道多普勒超声心动图图像和跨瓣血流速度信号。我们专注于在临床环境中使用多普勒超声心动图常规测量的三个基本变量：最大速度（Vmax）、平均速度（Vmean）和速度时间积分（VTI）。两种方法之间的比较显示出非常好的一致性。两种方法之间发现了一个很小的偏差值（Vmax 之间为 -3.9%至 0.5%，Vmean 之间为 -4.6%至-1.4%，VTI 之间为-3.6%至 4.4%）。此外，计算时间很短，大约 5 秒。因此，这种新方法应用于 DEVM 可以提供一种有用的工具来消除 DEVM 相关的观察者内和观察者间变异性，从而提高心血管疾病诊断的准确性。与标准手动追踪方法相比，这种自动方法还可以使超声心动图医师在更短的时间内完成这些测量。从实际的角度来看，开发的模型可以很容易地在标准超声心动图系统中实现。
