TY - JOUR AU - Yongping，梁au娟，张au周，Ping AU - Yongfeng，赵au - Liu，文刚AU - Shi, Yifan PY - 2020 DA - 20/5/5 TI -四平面法在乳腺病变超声计算机辅助诊断中的评价:前瞻性单中心研究JO - JMIR Med Inform SP - e18251 VL - 8 IS - 5kw -超声检查KW -乳腺肿瘤KW -乳腺成像报告和数据系统(双rad) KW -乳腺肿瘤诊断KW -癌症筛查KW -计算机辅助诊断KW -乳腺癌AB -背景:计算机辅助诊断(CAD)是一种可以帮助放射科医生通过超声检查诊断乳腺病变的工具。先前的研究表明，CAD可以帮助降低放射科医生漏诊的发生率。然而，使用诊断平面将CAD应用于乳腺病变的最佳方法尚未得到评估。目的:本研究的目的是比较不同经验水平的放射科医生在使用CAD和四平面法检测乳腺肿瘤时的表现。方法:从2018年11月至2019年10月，我们在研究中招募了以乳房肿块为最突出症状的患者。我们安排了2名超声放射科医生(分别有1年和5年的经验)在没有CAD的情况下读取乳房超声图像，然后在应用CAD和四平面方法的情况下进行第二次读取。然后，我们比较了两种读数(无CAD和有CAD)的阅读器的诊断性能。对配对数据采用McNemar检验进行统计分析。结果:本研究共纳入331例患者(平均年龄43.88岁，范围17-70岁，SD 12.10)，包括512个病灶(平均直径1.85厘米，SD 1.19; range 0.26-9.5); 200/512 (39.1%) were malignant, and 312/512 (60.9%) were benign. For CAD, the area under the receiver operating characteristic curve (AUC) improved significantly from 0.76 (95% CI 0.71-0.79) with the cross-planes method to 0.84 (95% CI 0.80-0.88; P<.001) with the quadri-planes method. For the novice reader, the AUC significantly improved from 0.73 (95% CI 0.69-0.78) for the without-CAD mode to 0.83 (95% CI 0.80-0.87; P<.001) for the combined-CAD mode with the quadri-planes method. For the experienced reader, the AUC improved from 0.85 (95% CI 0.81-0.88) to 0.87 (95% CI 0.84-0.91; P=.15). The kappa indicating consistency between the experienced reader and the novice reader for the combined-CAD mode was 0.63. For the novice reader, the sensitivity significantly improved from 60.0% for the without-CAD mode to 79.0% for the combined-CAD mode (P=.004). The specificity, negative predictive value, positive predictive value, and accuracy improved from 84.9% to 87.8% (P=.53), 76.8% to 86.7% (P=.07), 71.9% to 80.6% (P=.13), and 75.2% to 84.4% (P=.12), respectively. For the experienced reader, the sensitivity improved significantly from 76.0% for the without-CAD mode to 87.0% for the combined-CAD mode (P=.045). The NPV and accuracy moderately improved from 85.8% and 86.3% to 91.0% (P=.27) and 87.0% (P=.84), respectively. The specificity and positive predictive value decreased from 87.4% to 81.3% (P=.25) and from 87.2% to 93.0% (P=.16), respectively. Conclusions: S-Detect is a feasible diagnostic tool that can improve the sensitivity, accuracy, and AUC of the quadri-planes method for both novice and experienced readers while also improving the specificity for the novice reader. It demonstrates important application value in the clinical diagnosis of breast cancer. Trial Registration: ChiCTR.org.cn 1800019649; http://www.chictr.org.cn/showproj.aspx?proj=33094 SN - 2291-9694 UR - https://medinform.www.mybigtv.com/2020/5/e18251 UR - https://doi.org/10.2196/18251 UR - http://www.ncbi.nlm.nih.gov/pubmed/32369039 DO - 10.2196/18251 ID - info:doi/10.2196/18251 ER -