S-DetectTM classification technique in diagnosis of BI-RADS 4 breast masses
10.13929/j.issn.1003-3289.2020.09.010
- VernacularTitle: S-DetectTM分类技术诊断BI-RADS 4类乳腺肿块
- Author:
Boyuan XING
1
Author Information
1. People's Hospital of China Three Gorges University, The First People's Hospital of Yichang
- Publication Type:Journal Article
- Keywords:
Breast imaging reporting and data system;
Breast neoplasms;
S-DetectTM classification;
Ultrasonography
- From:
Chinese Journal of Medical Imaging Technology
2020;36(9):1319-1323
- CountryChina
- Language:Chinese
-
Abstract:
Objective: To explore the diagnostic value of S-DetectTM classification technique for benign and malignant breast imaging reporting and data system (BI-RADS) 4 breast masses. Methods: Totally 94 patients with 104 two-dimensional ultrasound diagnosed BI-RADS 4 breast masses were examined using S-DetectTM classification technique. Taken pathological results as the gold standards, the diagnostic values of S-DetectTM classification technology, BI-RADS classification alone and the combination of them of benign and malignant breast BI-RADS 4 masses were observed. Results: There were 41 benign and 63 malignant ones among all 104 BI-RADS 4 breast masses. The sensitivity (SE) of S-DetectTM classification technique for diagnosing breast BI-RADS 4a mass was 66.67%, specificity (SP) was 89.29%, positive predictive value (PPV) was 57.14%, negative predictive value (NPV) was 92.59%, of BI-RADS 4b masses was 90.91%, 60.00%, 88.24% and 66.67%, of breast BI-RADS 4c mass was 95.83%, 66.67%, 95.83% and 66.67%, respectively. SE, SP and accuracy of combination of S-DetectTM classification and BI-RADS classification for diagnosing breast masses were significantly higher than those of BI-RADS classification and S-DetectTM classification technique alone (all P<0.05). Conclusion: S-DetectTM classification technique was valuable for judging BI-RADS 4a benign masses as well as BI-RADS 4b and BI-RADS 4c malignant masses. S-DetectTM classification technology combined with BI-RADS classification could significantly improve the diagnostic value of identifying benign and malignant BI-RADS 4 breast masses.
