Choi Ji-Hye, Kang Bong Joo, Baek Ji Eun, Lee Hyun Sil, Kim Sung Hun
Department of Radiology, Bucheon St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Bucheon, Korea.
Department of Radiology, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Korea.
Ultrasonography. 2018 Jul;37(3):217-225. doi: 10.14366/usg.17046. Epub 2017 Aug 14.
The purpose of this study was to evaluate the usefulness of applying computer-aided diagnosis (CAD) to breast ultrasound (US), depending on the operator's experience with breast imaging.
Between October 2015 and January 2016, two experienced readers obtained and analyzed the grayscale US images of 200 cases according to the Breast Imaging Reporting and Data System (BI-RADS) lexicon and categories. They additionally applied CAD (S-Detect) to analyze the lesions and made a diagnostic decision subjectively, based on grayscale US with CAD. For the same cases, two inexperienced readers analyzed the grayscale US images using the BI-RADS lexicon and categories, added CAD, and came to a subjective diagnostic conclusion. We then compared the diagnostic performance depending on the operator's experience with breast imaging.
The sensitivity values for the experienced readers, inexperienced readers, and CAD (for experienced and inexperienced readers) were 91.7%, 75%, 75%, and 66.7%, respectively. The specificity values for the experienced readers, inexperienced readers, and CAD (for experienced and inexperienced readers) were 76.6%, 71.8%, 78.2%, and 76.1%, respectively. When diagnoses were made subjectively in combination with CAD, the specificity significantly improved (76.6% to 80.3%) without a change in the sensitivity (91.7%) in the experienced readers. After subjective combination with CAD, the sensitivity and specificity improved in the inexperienced readers (75% to 83.3% and 71.8% to 77.1%). In addition, the area under the curve improved for both the experienced and inexperienced readers (0.84 to 0.86 and 0.73 to 0.8) after the addition of CAD.
CAD is more useful for less experienced readers. Combining CAD with breast US led to improved specificity for both experienced and inexperienced readers.
本研究旨在根据操作者的乳腺成像经验,评估将计算机辅助诊断(CAD)应用于乳腺超声(US)的实用性。
2015年10月至2016年1月期间,两名经验丰富的阅片者根据乳腺影像报告和数据系统(BI-RADS)词典及分类获取并分析了200例病例的灰阶超声图像。他们还应用CAD(S-Detect)分析病变,并基于灰阶超声与CAD主观做出诊断决策。对于相同病例,两名经验不足的阅片者使用BI-RADS词典及分类分析灰阶超声图像,添加CAD,并得出主观诊断结论。然后,我们根据操作者的乳腺成像经验比较了诊断性能。
经验丰富的阅片者、经验不足的阅片者以及CAD(针对经验丰富和经验不足的阅片者)的敏感度值分别为91.7%、75%、75%和66.7%。经验丰富的阅片者、经验不足的阅片者以及CAD(针对经验丰富和经验不足的阅片者)的特异度值分别为76.6%、71.8%、78.2%和76.1%。当结合CAD进行主观诊断时,经验丰富的阅片者的特异度显著提高(从76.6%提高到80.3%),而敏感度不变(91.7%)。在与CAD进行主观结合后,经验不足的阅片者的敏感度和特异度均有所提高(从75%提高到83.3%,从71.8%提高到77.1%)。此外,添加CAD后,经验丰富和经验不足的阅片者的曲线下面积均有所改善(从0.84提高到0.86,从0.73提高到0.8)。
CAD对经验较少的阅片者更有用。将CAD与乳腺超声相结合可提高经验丰富和经验不足的阅片者的特异度。