Paper
25 March 2016 Radiogenomic analysis of breast cancer: dynamic contrast enhanced - magnetic resonance imaging based features are associated with molecular subtypes
Shijian Wang, Ming Fan, Juan Zhang, Bin Zheng, Xiaojia Wang, Lihua Li
Author Affiliations +
Abstract
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.
© (2016) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Shijian Wang, Ming Fan, Juan Zhang, Bin Zheng, Xiaojia Wang, and Lihua Li "Radiogenomic analysis of breast cancer: dynamic contrast enhanced - magnetic resonance imaging based features are associated with molecular subtypes", Proc. SPIE 9789, Medical Imaging 2016: PACS and Imaging Informatics: Next Generation and Innovations, 978904 (25 March 2016); https://doi.org/10.1117/12.2217658
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KEYWORDS
Breast cancer

Breast

Magnetic resonance imaging

Radium

Image segmentation

Radon

Statistical analysis

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