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Quantitatively Characterizing the Textural Features of Sonographic Images for Breast Cancer With Histopathologic Correlation
Author(s) -
Chen Shao-Jer,
Cheng Kuo-Sheng,
Dai Yuan-Chang,
Sun Yung-Nien,
Chen Yen-Ting,
Chang Ku-Yaw,
Yu Sung-Nien,
Chang Tsai-Wang,
Tsai Hong-Ming,
Hsien Chin-Chiang
Publication year - 2005
Publication title -
journal of ultrasound in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.574
H-Index - 91
eISSN - 1550-9613
pISSN - 0278-4297
DOI - 10.7863/jum.2005.24.5.651
Subject(s) - medicine , breast cancer , correlation , radiology , pathology , cancer , geometry , mathematics
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.