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- Title
The value of S-Detect for the differential diagnosis of breast masses on ultrasound: a systematic review and pooled meta-analysis.
- Authors
Jun Li; Tian Sang; Wen-Hui Yu; Meng Jiang; Shu-Yan Huang; Chun-Li Cao; Ming Chen; Yu-Wen Cao; Xin-Wu Cui; Dietrich, Christoph F.; Li, Jun; Sang, Tian; Yu, Wen-Hui; Jiang, Meng; Hunag, Shu-Yan; Cao, Chun-Li; Chen, Ming; Cao, Yu-Wen; Cui, Xin-Wu
- Abstract
<bold>Aim: </bold>To evaluate the value of S-Detect (a computer aided diagnosis system using deep learning) in breast ultrasound (US) for discriminating benign and malignant breast masses.<bold>Material and Methods: </bold>A literature search was performed and relevant studies using S-Detect for the differential diagnosis of breast masses were selected. The quality of included studies was assessed using a Quality Assessment of Diagnostic Accuracy Studies (QUADAS) questionnaire. Two review authors independently searched the articles and assessed the eligibility of the reports.<bold>Results: </bold>A total of ten studies were included in the meta-analysis. The pooled estimates of sensitivity and specificity were 0.82 (95%CI: 0.77-0.87) and 0.86 (95%CI: 0.76-0.92), respectively. In addition, the diagnostic odds ratios, positive likelihood ratio and negative likelihood ratio were 28 (95%CI: 16- 49), 5.7 (95%CI: 3.4-9.5), and 0.21 (95%CI: 0.16-0.27), respectively. Area under the curve was 0.89 (95%CI: 0.86-0.92). No significant publication bias was observed.<bold>Conclusions: </bold>S-Detect exhibited a favourable diagnostic value in assisting physicians discriminating benign and malignant breast masses and it can be considered as a useful complement for conventional US.
- Subjects
BREAST ultrasound; DIFFERENTIAL diagnosis; BREAST; META-analysis; PUBLICATION bias; DEEP learning; ODDS ratio; ULTRASONIC imaging; CONFIDENCE intervals; SYSTEMATIC reviews; BREAST tumors
- Publication
Medical Ultrasonography, 2020, Vol 22, Issue 2, p211
- ISSN
1844-4172
- Publication type
journal article
- DOI
10.11152/mu-2402