Radiogenomic analysis of breast cancer: Dynamic contrast enhanced - Magnetic resonance imaging based features are associated with molecular subtypes
2016
Breast cancer is one of the most common malignant tumor with upgrading incidence in females. The key to
decrease the mortality is early diagnosis and reasonable treatment. Molecular classification could provide better
insights into patient-directed therapy and prognosis prediction of breast cancer. It is known that different molecular
subtypes have different characteristics in magnetic resonance imaging (MRI) examination. Therefore, we assumed
that imaging features can reflect molecular information in breast cancer. In this study, we investigated associations
between dynamic contrasts enhanced MRI (DCE-MRI) features and molecular subtypes in breast cancer. Sixty
patients with breast cancer were enrolled and the MR images were pre-processed for noise reduction, registration
and segmentation. Sixty-five dimensional imaging features including statistical characteristics, morphology, texture
and dynamic enhancement in breast lesion and background regions were semiautomatically extracted. The
associations between imaging features and molecular subtypes were assessed by using statistical analyses,
including univariate logistic regression and multivariate logistic regression. The results of multivariate regression
showed that imaging features are significantly associated with molecular subtypes of Luminal A (p=0.00473),
HER2-enriched (p=0.00277) and Basal like (p=0.0117), respectively. The results indicated that three molecular
subtypes are correlated with DCE-MRI features in breast cancer. Specifically, patients with a higher level of
compactness or lower level of skewness in breast lesion are more likely to be Luminal A subtype. Besides, the
higher value of the dynamic enhancement at T1 time in normal side reflect higher possibility of HER2-enriched
subtype in breast cancer.
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