MR Imaging Findings and Texture Analysis of Pure and Mixed Mucinous Breast Carcinoma
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Purpose: To evaluate the ability of magnetic resonance imaging (MRI) findings and texture features to differentiate between pure and mixed subtypes of mucinous breast carcinoma.Methods: This retrospective study included 136 patients who were surgically diagnosed with mucinous breast carcinoma and underwent pre-treatment breast MRI between January 2008 and December 2020. All clinicopathological and MRI features were reviewed. For texture analysis, regions of interest of the tumors were drawn manually on T2-weighted images and first-subtraction T1-weighted images. Texture feature extraction and analysis were conducted using open-source 3D slicer software. Univariate and multivariate analyses were used to identify significant MRI findings and texture features to differentiate between the two subtypes. To evaluate the diagnostic performance of the texture features, a receiver operating characteristic curve analysis was conducted.Results: Among the MRI findings, very high signal intensity on T2-weighted images was significantly associated with pure mucinous breast carcinoma (odds ratio=5.23, <i>p</i>=0.001). The homogeneity and skewness texture features from T2-weighted imaging showed statistically significant differences between pure and mixed subtypes, and the areas under the receiver operating curve were 0.749 and 0.815, respectively.Conclusion: Signal intensity and texture features on T2- weighted images derived from breast MRI can assist in the differential diagnosis of pure and mixed types of mucinous breast carcinoma.
Abstract
Purpose: To evaluate the ability of magnetic resonance imaging (MRI) findings and texture features to differentiate between pure and mixed subtypes of mucinous breast carcinoma.Methods: This retrospective study included 136 patients who were surgically diagnosed with mucinous breast carcinoma and underwent pre-treatment breast MRI between January 2008 and December 2020. All clinicopathological and MRI features were reviewed. For texture analysis, regions of interest of the tumors were drawn manually on T2-weighted images and first-subtraction T1-weighted images. Texture feature extraction and analysis were conducted using open-source 3D slicer software. Univariate and multivariate analyses were used to identify significant MRI findings and texture features to differentiate between the two subtypes. To evaluate the diagnostic performance of the texture features, a receiver operating characteristic curve analysis was conducted.Results: Among the MRI findings, very high signal intensity on T2-weighted images was significantly associated with pure mucinous breast carcinoma (odds ratio=5.23, <i>p</i>=0.001). The homogeneity and skewness texture features from T2-weighted imaging showed statistically significant differences between pure and mixed subtypes, and the areas under the receiver operating curve were 0.749 and 0.815, respectively.Conclusion: Signal intensity and texture features on T2- weighted images derived from breast MRI can assist in the differential diagnosis of pure and mixed types of mucinous breast carcinoma.
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