Application of computer-aided diagnosis to predict malignancy in BI-RADS 3 breast lesions
Ping He,
Wen Chen,
Ming-Yu Bai,
Jun Li,
Qing-Qing Wang,
Li-Hong Fan,
Jian Zheng,
Chun-Tao Liu,
Xiao-Rong Zhang,
Xi-Rong Yuan,
Peng-Jie Song,
Li-Gang Cui
Affiliations
Ping He
Department of Ultrasound, Peking University Third Hospital, 49 North Garden Rd., Beijing, 100191, China
Wen Chen
Department of Ultrasound, Peking University Third Hospital, 49 North Garden Rd., Beijing, 100191, China
Ming-Yu Bai
Department of Ultrasound, Peking University Third Hospital, 49 North Garden Rd., Beijing, 100191, China
Jun Li
Department of Ultrasound, The First Affiliated Hospital of Medical College of Shihezi University, 107 North Second Rd., Shihezi, 832008, Xinjiang, China
Qing-Qing Wang
Department of Breast Ultrasonography, Center for Diagnosis and Treatment of Breast Diseases, Yili Maternity and Child Health Hospital, Sichuan Road, Economic Cooperation Zone, Yili Kazakh Autonomous Prefecture, Xinjiang Uyghur Autonomous Region, China
Li-Hong Fan
Department of Ultrasound, Jinzhong First People's Hospital, 689 South Huitong Rd. Yuci District 030600, Jinzhong City, Shanxi Province, China
Jian Zheng
Ultrasound Department of the Second Affiliated Hospital, School of Medicine, The Chinese University of Hong Kong, Shenzhen & Longgang District People's Hospital of Shenzhen, Shenzhen, 518172, China
Chun-Tao Liu
Department of Ultrasound, Liaocheng Dongchangfu District Maternal and Child Care Service Center, 129 Zhenxing West Rd., Liaocheng, 252000, Shandong, China
Xiao-Rong Zhang
Department of Ultrasound, Beijing HaiDian Hospital, 29 Zhongguanchun Rd., Beijing, 100080, China
Xi-Rong Yuan
Department of Ultrasound, The Second People's Hospital of Zhangqiu District, Jinan, Shandong, Ji Nan Zhang Qiu, 250200, China
Peng-Jie Song
Department of Ultrasound, Port Hospital of Hebei Port Group Co. LTD, 57 Dongshan Street, Haigang District, Qinhuangdao City, Hebei Province, China
Li-Gang Cui
Department of Ultrasound, Peking University Third Hospital, 49 North Garden Rd., Beijing, 100191, China; Corresponding author.
Purpose: To evaluate the ability of computer-aided diagnosis (CAD) system (S-Detect) to identify malignancy in ultrasound (US) -detected BI-RADS 3 breast lesions. Materials and methods: 148 patients with 148 breast lesions categorized as BI-RADS 3 were included in the study between January 2021 and September 2022. The malignancy rate, accuracy, sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and area under the curve (AUC) were calculated. Results: In this study, 143 breast lesions were found to be benign, and 5 breast lesions were malignant (malignancy rate, 3.4 %, 95 % confidence interval (CI): 0.5–6.3). The malignancy rate rose significantly to 18.2 % (4/22, 95 % CI: 2.1–34.3) in the high-risk group with a “possibly malignant” CAD result (p = 0.017). With a “possibly benign” CAD result, the malignancy rate decreased to 0.8 % (1/126, 95 % CI: 0–2.2) in the low-risk group (p = 0.297). The AUC, sensitivity, specificity, accuracy, PPV, and NPV of the CAD system in BI-RADS 3 breast lesions were 0.837 (95 % CI: 77.7–89.6), 80.0 % (95 % CI: 73.6–86.4), 87.4 % (95 % CI: 82.0–92.7), 87.2 % (95 % CI: 81.8–92.6), 18.2 % (95 % CI: 2.1–34.3) and 99.2 % (95 % CI: 97.8–100.0), respectively. Conclusions: CAD system (S-Detect) enables radiologists to distinguish a high-risk group and a low-risk group among US-detected BI-RADS 3 breast lesions, so that patients in the low-risk group can receive follow-up without anxiety, while those in the high-risk group with a significantly increased malignancy rate should actively receive biopsy to avoid delayed diagnosis of breast cancer.
