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| Prediction of Near-Term Breast Cancer Risk in Mediolateral Oblique View of Mammography |
| Li Yane1, Zhang Peng1, Fan Ming, Zheng Bin1,2, Li Lihua1* |
1College of Life Information Science and Instrument Engineering, Hangzhou Dianzi University, Hangzhou 310018, China
2School of Electrical and Computer Engineering, University of Oklahoma, Oklahoma, Tulsa, OK 74135, USA |
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Abstract This study proposed a model for the prediction of near-term breast cancer risk in mediolateral oblique view (MLO) of negative full-field digital mammography (FFDM) images based on local and global region bilateral asymmetry features. The retrospective dataset included series of two sequential FFDM examinations of 556 women. In the “current” examination 278 women were diagnosed with pathology verified cancers and 278 cases remained negative. Patients’ age for breast cancers and negative cases were matched. After region of interest include local and global regions were segmented, spatial distribution, structural similarity and positional information related features were extracted. After decorrelation process, 7 features with Spearman correlations >0.6 were excluded and 78 features were remained for further analyses. Next, a short-term breast cancer risk prediction model was built using a leave-one-case-out cross-validation method to predict the likelihood of each woman having image-detectable cancer in the next sequential mammography screening. The computed areas under a receiver operating characteristic curves (AUC) was 0.6667±0.0226 with the specificity and sensitivity were 0.6906 and 0.5216 respectively when combined global-and local-based features. The odds ratio values was increased with a significantly increasing trend in slope (P=0.002033) as the model-generated risk score increased. In addition, for the three age groups of 37-49, 50-65 and 66-87 years old, the AUC values were 0.681 0±0.043 2,0.671 6±0.030 0 and 0.678 2±0.054 7 with the specificity were 0.702 7, 0.694 3 and0.723 4 and sensitivity were 0.554 1, 0.490 4 and 0.574 5 respectively. And AUC values of0.654 5 and 0.694 4 were yielded for BIRADS 2 and BIRADS 3, respectively. With the specificity were0.676 2 and 0.733 3 and sensitivity were 0.522 9 and 0.536 9 for BIRADS 2 and BIRADS 3, respectively. This study demonstrated the potential of bilateral asymmetry features extracted from MLO view mammography to assist the prediction of near-term breast cancer risk.
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Received: 05 September 2017
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