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Quantitatively Characterizing the Textural Features of Sonographic Images for Breast Cancer With Histopathologic Correlation

Institute of Biomedical Engineering (S.-J.C., K.-S.C.) and Department of Computer Science and Information Engineering (Y.-N.S.), National Cheng Kung University, Tainan, Taiwan; Department of Radiology, Buddhist Dalin Tzu Chi General Hospital, Chia-Yi, Taiwan (S.-J.C.); Department of Pathology, Chia-Yi Christian Hospital, Chia-Yi, Taiwan (Y.-C.D.); Department of Electrical Engineering, Southern Taiwan University of Technology, Tainan, Taiwan (Y.-T.C.); Department of Computer Science and Information Engineering, Da-Yeh University, Changhua, Taiwan (K.-Y.C.); Department of Electrical Engineering, National Chung Cheng University, Chia-Yi, Taiwan (S.-N.Y.); and Departments of Surgery (T.-W.C.) and Radiology (H.-M.T., C.-C.H.), National Cheng Kung University Hospital, Tainan, Taiwan.

Address correspondence to Kuo-Sheng Cheng, PhD, Institute of Biomedical Engineering, National Cheng Kung University, 1 Ta-Hsueh Rd, Tainan 701, Taiwan. E-mail: kscheng{at}mail.ncku.edu.tw (K.-S.C.); chensj{at}mail.ncku.edu.tw (S.-J.C.)

Objective. In this study, quantitative characterization of sonographic image texture and its correlation with histopathologic findings was developed for facilitating clinical diagnosis. A statistical feature matrix was applied to quantify the texture difference (ie, the dissimilarity) of the sonographic images for malignant and benign breast tumors. Methods. Thirty-three patients were recruited for this study. Imaging was performed on a commercially available sonographic imaging system in clinical use. The parameters used for image acquisition were kept the same during clinical examination. Results. On the basis of dissimilarity values, 3 phenomena were noted in the relatively large malignancies studied. First, stellate carcinoma showed the least dissimilarity on sonographic images; second, circumscribed carcinoma showed the most dissimilarity; and third, malignant tissue mixed with fibrous and cellular parts (dense lymphocyte infiltration and prominent intraductal tumors) had dissimilarity values in between. Image textures with smaller dissimilarity values (especially for those values <4.4 in our study) are likely to be stellate carcinoma. Conclusions. From the experimental results, it is shown that the cellular and fibrous content with spatial distribution of breast masses determine the dissimilarity values on sonographic images. The dissimilarity may be used to quantitatively represent the image texture and is well correlated with the histopathologic description.

Key Words: breast neoplasm • histopathologic finding • sonographic images • textural analysis • tissue characterization

Abbreviations: H&E, hematoxylin-eosin • ROI, region of interest • SFM, statistical feature matrix • 2D, 2-dimensional

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