Peter T. Fwu1, Jeon-Hor. Chen1, 2, Siwa Chan3, Dah-Cherng Yeh4, Chin-Kai Chang2, Julian Kao1, Muqing Lin1, Orhan Nalcioglu1, Min-Ying L. Su1
1Center for Functional Onco-Imaging, Department of Radiological Sciences, University of California, Irvne, CA, United States; 2Department of Radiology, China Medical University Hospital, Taichung, Taiwan; 3Department of Radiology, Taichung Veterans General Hospital, Taichung, Taiwan; 4Department of Surgery, Taichung Veterans General Hospital, Taichung, Taiwan
The purpose is to develop a quantitative method to characterize the breast density pattern using 3D morphology and texture analysis for investigating its role in cancer risk prediction. Morphology is characterized by circularity, convexity, and irregularity; texture is characterized by coefficient of variation in signal intensity distribution and the GLCM matrix. The ability of analyzed parameters to differentiate between the central and the intermingled breast density patterns is evaluated by the ROC analysis. The results show that morphology parameters can reach AUC of 0.95, texture parameters have a lower AUC of 0.90, but combining them can yield AUC of 0.98.
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