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| DBT-based radiomics for differentiating benign and malignant breast lesions |
| JIANG Wen-yan1, NIU Shu-xian2, ZHANG Meng-yao2, CUI Lin-peng2, #br#
DONG Yue1, AI Hua1, ZHOU Xiao-ya3, YU Tao1, LUO Ya-hong1 |
1. Department of Imaging, Cancer Hospital of China Medical University, Liaoning Cancer Hospital & Institute, Shenyang 110042, China;
2. Department of Biomedical Engineering, China Medical University, Shenyang 110122, China;
3. College of Basic Medicine, Jining Medical University, Jining Shandong 272067, China |
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Abstract Objective: To evaluate the role of DBT-based radiomics in differentiating benign and malignant breast lesions. Methods: Breast DBT data of 160 patients were collected from Liaoning Cancer Hospital from September 2017 to April 2018 were analyzed. Radiomics features were extracted and analyzed. A nomogram model for distinguishing benign and malignant lesions was constructed. The clinical applicability of the nomogram was further evaluated by decision curve analysis. The predictive abilities of the models were evaluated by ROC curves and AUC values. Result: The AUC values of the constructed nomogram were 0.942(SEN=0.833, SPE=0.928) and 0.928(SEN=0.926, SPE=0.839) in the training and validation cohorts, respectively. The DCA analyses showed that our nomogram had good clinical value. Conclusion: Our nomogram model based on breast DBT image features has great potential in non-invasive distinguishing benign and malignant lesions.
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Received: 22 October 2019
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