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[二维超声心动图中的自动轮廓检测——一般患者群体研究]

[Automatic contour detection in the 2-dimensional echocardiogram--studies in a general patient population].

作者信息

Grube E, Backs A, Backs B, Lüderitz B

出版信息

Z Kardiol. 1985 Aug;74(8):445-52.

PMID:4049995
Abstract

In order to test the application of an endocardial contour finding algorithm in apical projections we examined 56 consecutive patients by 2-D echocardiography. According to the quality of the endocardial definition we graded the total patient population in 4 qualities, grade I being the best and grade IV being the worst echocardiographic image with multiple extracavitary and intracavitary artefacts. Following manual and automatic detection of LV endocardium in end-systole and end-diastole by 2 observers we calculated LV areas (cm2), volumes (ml), ejection fraction (%) and regional wall motion (% radial shortening and % area shrinkage) and determined the reproducibility of the two different endocardial definitions. In all echocardiograms with good endocardial visualisation (grade I and II; n = 31, 55%), in 9 out of 15 patients with grade III and 4 out of 10 patients with grade IV echocardiograms we could successfully apply the contour finding algorithm. The comparison between automatically and manually detected contours showed good correlations with small standard errors; however the reproducibility of data expressed by the interobserver variability (V) calculated on the basis of automatically found contours was significantly better as compared to the manually derived contours. (V manual contour = 4.8-8.5 versus automatic contours 0.63-0.68). The systolic volumes (manual versus auto) correlated with r = 0.93, SEE 8.3 ml; the end-diastolic volumes (manual versus auto) with r = 0.90, SEE 11.3 ml, the ejection fraction (manual versus auto) with r = 0.93, SEE 5.1%. The determination of regional LV wall motion demonstrated an agreement in 91% and a discrepancy in 9% of regions.(ABSTRACT TRUNCATED AT 250 WORDS)

摘要

为了测试心内膜轮廓查找算法在心尖投影中的应用,我们通过二维超声心动图检查了56例连续患者。根据心内膜清晰度的质量,我们将全部患者分为4个等级,I级为最佳,IV级为最差,IV级超声心动图图像存在多个腔外和腔内伪像。在两名观察者手动和自动检测收缩末期和舒张末期左心室心内膜后,我们计算了左心室面积(cm²)、容积(ml)、射血分数(%)和局部室壁运动(%径向缩短和%面积缩小),并确定了两种不同心内膜定义的可重复性。在所有心内膜可视化良好的超声心动图中(I级和II级;n = 31,55%),在15例III级患者中的9例以及10例IV级超声心动图患者中的4例中,我们能够成功应用轮廓查找算法。自动检测轮廓与手动检测轮廓之间的比较显示出良好的相关性,标准误差较小;然而,基于自动找到的轮廓计算的观察者间变异性(V)所表示的数据可重复性明显优于手动得出的轮廓。(手动轮廓的V = 4.8 - 8.5,而自动轮廓的V = 0.63 - 0.68)。收缩期容积(手动与自动)的相关性r = 0.93,标准误8.3 ml;舒张末期容积(手动与自动)的相关性r = 0.90,标准误11.3 ml,射血分数(手动与自动)的相关性r = 0.93,标准误5.1%。左心室局部室壁运动的测定显示,91%的区域一致,9%的区域存在差异。(摘要截断于250字)

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