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首页> 外文期刊>JMIR Medical Informatics >Evaluation of the Quadri-Planes Method in Computer-Aided Diagnosis of Breast Lesions by Ultrasonography: Prospective Single-Center Study
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Evaluation of the Quadri-Planes Method in Computer-Aided Diagnosis of Breast Lesions by Ultrasonography: Prospective Single-Center Study

机译：超声检查对乳房病变的计算机辅助诊断中的Quadri-Planes方法评价：前瞻性单中心研究

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Background Computer-aided diagnosis (CAD) is a tool that can help radiologists diagnose breast lesions by ultrasonography. Previous studies have demonstrated that CAD can help reduce the incidence of missed diagnoses by radiologists. However, the optimal method to apply CAD to breast lesions using diagnostic planes has not been assessed. Objective The aim of this study was to compare the performance of radiologists with different levels of experience when using CAD with the quadri-planes method to detect breast tumors. Methods From November 2018 to October 2019, we enrolled patients in the study who had a breast mass as their most prominent symptom. We assigned 2 ultrasound radiologists (with 1 and 5 years of experience, respectively) to read breast ultrasonography images without CAD and then to perform a second reading while applying CAD with the quadri-planes method. We then compared the diagnostic performance of the readers for the 2 readings (without and with CAD). The McNemar test for paired data was used for statistical analysis. Results A total of 331 patients were included in this study (mean age 43.88 years, range 17-70, SD 12.10), including 512 lesions (mean diameter 1.85 centimeters, 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.
机译：背景技术计算机辅助诊断（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。以前的研究表明，CAD可以帮助减少放射科医生错过诊断的发病率。然而，尚未评估使用诊断平面将CAD应用于乳房病变的最佳方法。客观本研究的目的是在使用CAD与Quadri-Planes方法中使用CAD以检测乳腺肿瘤时比较放射科学家的性能。方法从2018年11月到2019年10月，我们注册了患者患者患有乳房质量的患者，作为他们最突出的症状。我们分配了2位超声放射科医生（分别有1和5年的经验），以读取没有CAD的乳房超声图像，然后在用Quadri-Planes方法应用CAD的同时执行第二次读数。然后，我们将读者的诊断性能与2读数（无关和CAD）进行比较。配对数据的McNemar测试用于统计分析。结果共有331名患者纳入本研究（平均年龄为43.88岁，17-70，SD 12.10），包括512个病变（平均直径1.85厘米，SD 1.19;范围0.26-9.5）; 200/512（39.1％）是恶性的，312/512（60.9％）是良性的。对于CAD，接收器操作特征曲线（AUC）下的区域从0.76（95％CI 0.71-0.79）显着改善，横穿速度为0.84（95％CI 0.80-0.88; P <.001） -Planes方法。对于新手读者，AUC从0.73（95％CI 0.69-0.78）显着提高到无需CAD模式至0.83（95％CI 0.80-0.87; P <.001），其中组合CAD模式与Quadri-飞机方法。对于经验丰富的读者，AUC从0.85（95％CI 0.81-0.88）提高至0.87（95％CI 0.84-0.91; P = .15）。表示有经验读者和组合CAD模式的新手读者之间的一致性的Kappa为0.63。对于新手读者，敏感度从无需CAD模式的60.0％显着提高到组合CAD模式的79.0％（P = .004）。特异性，消极预测值，阳性预测值和精度从84.9％提高到87.8％（p = .53），76.8％至86.7％（p = .07），71.9％至80.6％（p = .13）分别为75.2％至84.4％（p = .12）。对于经验丰富的读者，敏感度从没有CAD模式的76.0％提高到组合CAD模式的87.0％（P = .045）。 NPV和精度分别适度提高85.8％和86.3％至91.0％（P = .27）和87.0％（P = .84）。特异性和阳性预测值分别从87.4％降至81.3％（p = .25），分别为87.2％至93.0％（p = .16）。结论S检测是可行的诊断工具，可以提高新手和经验丰富的读者的Quadri-Planes方法的灵敏度，准确度和AUC，同时还提高了新手读者的特异性。它展示了乳腺癌临床诊断中的重要应用价值。

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