Development and validation of a transformer-based CAD model for improving the consistency of BI-RADS category 3–5 nodule classification among radiologists: a multiple center study

作者：Hongtao Ji, Qiang Zhu, Teng Ma, Yun Cheng, Shuai Zhou, Wei Ren, Huilian Huang, Wen He, Haitao Ran, Litao Ruan, Yanli Guo, Jiawei Tian, Chen Wu, Luzeng Chen, Zhiyuan Wang, Qi Zhou, Lijuan Niu, Wei Zhang, Ruimin Yang, Qin Chen, Ruifang Zhang, Hui Wang, Li Li, Minghui Liu, Fang Nie, Aiyun Zhou · 发表于：Quantitative Imaging in Medicine and Surgery · 年份：2023 · DOI：10.21037/qims-22-1091 · 被引用次数：10 · 研究领域：Lung Cancer Diagnosis and Treatment、Radiation Dose and Imaging

Background: Significant differences exist in the classification outcomes for radiologists using ultrasonography-based Breast Imaging Reporting and Data Systems for diagnosing category 3-5 (BI-RADS 3-5) breast nodules, due to a lack of clear and distinguishing image features. Consequently, this retrospective study investigated the improvement of BI-RADS 3-5 classification consistency using a transformer-based computer-aided diagnosis (CAD) model. Methods: Independently, 5 radiologists performed BI-RADS annotations on 21,332 breast ultrasonographic images collected from 3,978 female patients from 20 clinical centers in China. All images were divided into training, validation, testing, and sampling sets. The trained transformer-based CAD model was then used to classify test images, for which sensitivity (SEN), specificity (SPE), accuracy (ACC), area under the curve (AUC), and calibration curve were evaluated. Variations in these metrics among the 5 radiologists were analyzed by referencing BI-RADS classification results for the sampling test set provided by CAD to determine whether classification consistency (the k value), SEN, SPE, and ACC could be improved. Results: After the training set (11,238 images) and validation set (2,996 images) were learned by the CAD model, the classification ACC of the CAD model applied to the test set (7,098 images) was 94.89% in category 3, 96.90% in category 4A, 95.49% in category 4B, 92.28% in category 4C, and 95.45% in category 5 nodules. Base...