超声S-Detect分类技术在乳腺包块良恶性诊断中的应用价值

Application of S-Detect classification system in diagnosis of breast benign and malignant mass by ultrasound

目的探讨超声S-Detect分类技术在乳腺包块良恶性鉴别诊断中的应用价值。 方法选取我院2016年1－12月间经手术或病理穿刺活检证实的47例乳腺包块患者（共61个病灶）。所有病灶分别进行二维超声成像BI-RADS分类（由3类不同年资乳腺专科超声医师进行判别）以及计算机S-Detect分类，分别计算人为BI-RADS分类及S-Detect分类对乳腺包块良恶性诊断的敏感性、特异性、准确性、阳性预测值及阴性预测值。绘制各组的ROC曲线，比较ROC曲线下面积。 结果61个乳腺病灶中，病理证实良性病灶36个，恶性病灶25个。BI-RADS分类诊断的敏感性、特异性及准确性分别为：工作2年医师，69.4%、72.0%、70.5%；工作5年医师，64.0%、92.0%、75.4%；工作7年医师，69.4%、92.0%、78.7%。计算机S-Detect分类诊断敏感性、特异性及准确性分别为80.6%、96.0%、86.9%。S-Detect分类诊断特异性、准确性及阳性预测值均高于工作2年医师BI-RADS分类，差异均具有统计学意义（P〈0.05）。各组ROC曲线下面积分别为：工作2年医师，0.729 ；工作5年医师，0.786；工作7年医师，0.801；S-Detect分类，0.917。 结论与人工BI-RADS分类诊断相比，S-Detect分类在乳腺包块良恶性诊断中具有优势，尤其对于低年资医师，S-Detect分类有助于提高其诊断准确率。

ObjectiveTo investigate the value of S-Detect classification in differential diagnosis of breast mass. MethodsThe data of forty-seven patients with breast mass lesions （n=61） from our hospital during January to December in 2016 were retrospectively analyzed. Both the man-made BI-RADS classification （identified by three different specialist physicians with 2, 5 and 7 years of experience, respectively） and computer S-Detect classification were performed. The sensitivity, specificity, accuracy, positive predictive value and negative predictive value of the man-made BI-RADS classification and S-Detect classification of the benign or malignant diagnosis of breast lumps were calculated. The ROC curve was further plotted, and the area under the curve （AUC） of each group was compared, respectively. ResultsSixty-one breast mass lesions were confirmed 36 benign lesions and 25 malignant lesions by pathological biopsy. The sensitivity, specificity and accuracy of man-made BI-RADS classification were as follows： 2-year experience physicians 69.4%, 72.0% and 70.5%; 5-year experience physicians： 64.0%, 92.0% and 75.4%; 7-year experience physicians： 69.4%, 92.0% and 78.7%. The diagnostic sensitivity, specificity, and accuracy of S-Detect classification were 80.6%, 96.0% and 86.9%. The specificity, accuracy and positive predictive value of S-Detect classification were significantly higher than those of 2-year experience physicians by BI-RADS classification （P〈0.05）. The area under the ROC curve of each group was 0.729, 0.786 and 0.801 for 2, 5 and 7-year experience physicians, respectively, and 0.917 for S-Detect classification. ConclusionsCompared with the man-made BI-RADS classification, S-Detect classification has advantages in diagnosis of the benign or malignant of breast mass and is helpful to improve the accuracy of diagnosis, especially for junior physicians.