期刊
BREAST CANCER RESEARCH AND TREATMENT
卷 177, 期 2, 页码 419-426出版社
SPRINGER
DOI: 10.1007/s10549-019-05297-7
关键词
Breast lesions; MRI; Computer-aided diagnosis; Gaussian mixture; Random forest
类别
资金
- Postdoctoral Science Foundation of Ministry of Heilongjiang Province [LBH-Z17150]
PurposeThe present study aimed to determine suitable optimal classifiers and investigate the general applicability of computer-aided diagnosis (CAD) to compare magnetic resonance (MR)-CAD with MR imaging (MRI) in distinguishing benign from malignant solid breast masses.MethodsWe analyzed a total of 251 patients (mean age: 44.812.3years; range: 21-81years) with 274 breast masses (154 benign masses, 120 malignant masses) using a Gaussian mixture model and a random forest machine model for segmentation and classification.ResultsThe diagnostic performance of MRI alone and MRI plus CAD were compared with respect to sensitivity, specificity, and area under the curve (AUC), using receiver operating characteristic curve analysis. The discriminating power to detect malignancy using MR-CAD with an AUC of 0.955 (sensitivity was 95.8% and the specificity was 92.9%) was significantly higher than that of MRI alone with an AUC of 0.785 (sensitivity was 71.7% and the specificity was 85.7%).Conclusion CAD is feasible to differentiate breast lesions, and it can complement MRI, thereby making it easier to diagnose breast lesions and obviating the need for unnecessary biopsies.
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