Blahuta Jiri, Soukup Tomas, Jelinkova Monika, Bartova Petra, Cermak Petr, Herzig Roman, Skoloudik David
Institute of Computer Science, Faculty of Philosophy and Science, Silesian University in Opava, Opava, Czech Republic.
Biomed Pap Med Fac Univ Palacky Olomouc Czech Repub. 2014 Dec;158(4):621-7. doi: 10.5507/bp.2013.029. Epub 2013 Apr 22.
Recent studies report increased echogenicity of the substantia nigra (SN) in patients with Parkinson's disease (PD) using transcranial sonography (TCS). However, the main limitation to TCS is its dependence on the sonographer's experience. Experimental software for quantitative evaluation of the echogenic SN area was thus developed by us. The aim of this study was to test the reliability of the data using developed B-Mode Assist software in patients with parkinsonism and in healthy volunteers.
The SN was imaged from the right temporal bone window in mesencephalic plane using TCS. DICOM images of SN were saved, converted into JPEG format, encoded and processed. Two observers performed 3 automatic evaluations of the SN area (measurements of SN area in each gray scale intensity inside the region of interest) by counting the standard deviation of all 6 measurements using developed software. The average value of all 3 measurements of each observer was used for computing Cohen's kappa coefficient to determine inter-observer correlations. Cohen's kappa coefficients as an intra-observer correlation for observer 1 and observer 2 were counted from the first 2 measurements of both observers.
In total, 92 images were evaluated using this software. The mean of the standard deviations was 3.87; Cohen's kappa for intra-observer agreement of two observers were 0.947, and 0.943, resp.; Cohen's kappa for inter-observers agreement was 0.880. The agreement between visual and automatic detection of SN pathology was in 97.8% images. The sensitivity, specificity, positive and negative predictive values of automatic measurement were 100, 96.2, 95.1, 100%, resp.
The results show very reliable measurement of SN features using designed application with "almost perfect" inter-observer and intra-observer agreements.
近期研究报道，经颅超声检查（TCS）显示帕金森病（PD）患者黑质（SN）的回声增强。然而，TCS的主要局限性在于其依赖超声检查人员的经验。因此，我们开发了用于定量评估SN回声区域的实验软件。本研究的目的是在帕金森综合征患者和健康志愿者中，使用开发的B模式辅助软件测试数据的可靠性。
使用TCS从右颞骨窗在中脑平面成像SN。保存SN的DICOM图像，转换为JPEG格式，编码并处理。两名观察者通过使用开发的软件计算所有6次测量的标准差，对SN区域进行3次自动评估（测量感兴趣区域内每个灰度强度的SN区域）。每个观察者的所有3次测量的平均值用于计算科恩kappa系数，以确定观察者间的相关性。从两名观察者的前2次测量中计算科恩kappa系数作为观察者1和观察者2的观察者内相关性。
总共使用该软件评估了92幅图像。标准差的平均值为3.87；两名观察者的观察者内一致性的科恩kappa分别为0.947和0.943；观察者间一致性的科恩kappa为0.880。SN病变的视觉检测与自动检测之间的一致性在97.8%的图像中。自动测量的敏感性、特异性、阳性和阴性预测值分别为100%、96.2%、95.1%、100%。
结果表明，使用设计的应用程序对SN特征进行测量非常可靠，观察者间和观察者内的一致性“几乎完美”。
