The assistant diagnostic value of S-Detect technique in identification of breast cancer

Abstract

Objective To evaluate the assistant diagnostic value of S-Detect artificial intelligence system in differential diagnosis of benign and malignant breast tumors. Methods Clinical data and ultrasound images of 201 patients undergoing breast ultrasound examination in Tongji Hospital from March 2018 to May 2018 were acquired. Two-dimensional grayscale and color Doppler ultrasound images, S-Detect mode images and elastographic images of 220 breast lesions were analyzed. The BI-RADS categories of each lesion were divided into two groups: experienced group and random group.And according to whether to refer to S-Detect diagnostic results, the BI-RADS categories in experienced group were divided into A1 group and P1 group.In additional, the highest and lowest categories of the same tumor in random group were A2 group, and the diagnostic results of A2 group combining with S-Detect system were belonged to P2 group. The ROC curves were plotted and the area under the curve, sensitivity, specificity or the accuracy of the different groups were compared. Agreements of diagnostic results between different groups were analyzed by Kappa test. Results Out of 220 breast lesions, 181 lesions were benign and 39 lesions were malignant. The S-Detect artificial intelligence system had a relatively high diagnostic efficiency, and the sensitivity, specificity and accuracy of S-Detect classification were 92.3%, 90.6%, 90.9%, respectively. With its assistance, the specificity and accuracy in the experienced group had an increasing trend (A1 group: 86.7%, 88.6%; P1 group: 91.2%, 92.3%), and the diagnostic accuracy in random group was significantly improved (A2 group: 63.6%-85.5%; P2 group: 93.2%-94.1%). Both S-Detect system and elasticity score helped to improve the efficacy of ultrasound physicians in differential diagnosis of benign and malignant breast lesions. But there were differences in diagnostic performance and assistant diagnostic ability between the two techniques. Conclusions S-Detect technique contributes to the augment of diagnostic accuracy of ultrasound doctors in identifying breast cancer, improves the quality of random breast ultrasound examinations, and reduces missed diagnosis and misdiagnosis of breast examinations. Key words: Ultrasonography; Breast neoplasms; S-Detect techque