Association between breast cancer's prognostic factors and 3D textural features of non-contrast-enhanced T(1) weighted breast MRI

乳腺癌预后因素与非增强T1加权乳腺MRI三维纹理特征之间的关联

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Abstract

OBJECTIVES: The aim of this exploratory study was to evaluate whether three-dimensional texture analysis (3D-TA) features of non-contrast-enhanced T(1) weighted MRI associate with traditional prognostic factors and disease-free survival (DFS) of breast cancer. METHODS: 3D-T(1) weighted images from 78 patients with 81 malignant histopathologically verified breast lesions were retrospectively analysed using standard-size volumes of interest. Grey-level co-occurrence matrix (GLCM)-based features were selected for statistical analysis. In statistics the Mann-Whitney U and the Kruskal-Wallis tests, the Cox proportional hazards model and the Kaplan-Meier method were used. RESULTS: Tumours with higher histological grade were significantly associated with higher contrast (1 voxel: p = 0.033, 2 voxels: p = 0.036). All the entropy parameters showed significant correlation with tumour grade (p = 0.015-0.050) but there were no statistically significant associations between other TA parameters and tumour grade. The Nottingham Prognostic Index (NPI) was correlated with contrast and sum entropy parameters. A higher sum variance TA parameter was a significant predictor of shorter DFS. CONCLUSION: Texture parameters, assessed by 3D-TA from non-enhanced T(1) weighted images, indicate tumour heterogeneity but have limited independent prognostic value. However, they are associated with tumour grade, NPI, and DFS. These parameters could be used as an adjunct to contrast-enhanced TA parameters. ADVANCES IN KNOWLEDGE: 3D-TA of non-contrast enhanced T(1) weighted breast MRI associates with tumour grade, NPI, and DFS. The use of non-contrast 3D-TA parameters in adjunct with contrast-enhanced 3D-TA parameters warrants further research.

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