Huang Y-L, Chen H-Y
Department of Computer Science and Information Engineering, Tunghai University, Taichung, Taiwan.
Ultrasound Obstet Gynecol. 2007 Dec;30(7):1002-6. doi: 10.1002/uog.4102.
Adequately defining the anatomical and functional defects in women with stress urinary incontinence prior to surgical repair is essential. Differences in dynamic changes of the bladder neck on perineal ultrasound have been shown to be effective in differentiating between women with and those without urodynamic stress incontinence (USI). This study evaluated a system to diagnose USI with computer-aided vector-based perineal ultrasound.
We evaluated 48 women with lower urinary tract symptoms, of whom 36 were found to have USI, by urodynamic study and computer-aided vector-based perineal ultrasound. The function and morphology of the lower urinary tract were used as features in a multilayer perception (MLP) neural network classifier to distinguish between women with and those without USI. The k-fold cross-validation method was used to estimate the performance of the proposed computer-aided diagnosis (CAD) system.
The accuracy of the proposed CAD system for classifying USI was 91.7% (44/48), the sensitivity was 94.4% (34/36), the specificity was 83.3% (10/12), the positive predictive value was 94.4% (34/36) and the negative predictive value was 83.3% (10/12). The receiver-operating characteristics area index for the proposed CAD system was 0.941 +/- 0.034. The proposed CAD system differentiated USI effectively with perineal ultrasound.
Computer-aided vector-based perineal ultrasound is valuable in assessing anatomical changes of the bladder neck. Women with and those without USI can be distinguished using perineal sonographic analysis with the proposed CAD system. Because the MLP model is trainable, it could be optimized if a larger set of perineal ultrasound images and other useful features were supplied.
在手术修复前充分明确压力性尿失禁女性的解剖和功能缺陷至关重要。经会阴超声显示膀胱颈动态变化的差异可有效区分存在和不存在尿动力学压力性尿失禁（USI）的女性。本研究评估了一种利用基于计算机辅助向量的经会阴超声诊断USI的系统。
我们通过尿动力学研究和基于计算机辅助向量的经会阴超声评估了48名有下尿路症状的女性，其中36名被发现患有USI。下尿路的功能和形态被用作多层感知（MLP）神经网络分类器中的特征，以区分存在和不存在USI的女性。采用k折交叉验证方法评估所提出的计算机辅助诊断（CAD）系统的性能。
所提出的CAD系统对USI分类的准确率为91.7%（44/48），灵敏度为94.4%（34/36），特异度为83.3%（10/12），阳性预测值为94.4%（34/36），阴性预测值为83.3%（10/12）。所提出的CAD系统的受试者工作特征曲线下面积指数为0.941±0.034。所提出的CAD系统通过经会阴超声有效地区分了USI。
基于计算机辅助向量的经会阴超声在评估膀胱颈的解剖变化方面具有重要价值。使用所提出的CAD系统进行经会阴超声分析可以区分存在和不存在USI的女性。由于MLP模型是可训练的，如果提供更大的经会阴超声图像集和其他有用特征，它可以得到优化。
