Abstract #2562

Predicting Molecular Subtypes and Prognostic Factors of Breast Cancer Using Integrated Diffusion MRI

Muge Karaman^1,2, Yangyang Bu^3,4, Guangyu Dan^1,2, Zheng Zhong¹, Qingfei Luo¹, Shiwei Wang^3,4, Changyu Zhou^3,4, Weihong Hu^3,4, X. Joe Zhou^1,2,5, and Maosheng Xu^3,4

¹Center for MR Research, University of Illinois at Chicago, Chicago, IL, United States, ²Department of Biomedical Engineering, University of Illinois at Chicago, Chicago, IL, United States, ³The First School of Clinical Medicine of Zhejiang Chinese Medical University, Hangzhou, China, ⁴The First Affiliated Hospital of Zhejiang Chinese Medical University, Hangzhou, China, ⁵Departments of Radiology and Neurosurgery, University of Illinois at Chicago, Chicago, IL, United States

Synopsis

Keywords: Breast, Breast, molecular subtype prediction, heterogeneity, high-b-value diffusion MRIBreast cancer exhibits a wide spectrum of molecular subtypes and, which has important implications in treatment strategies. In this study, we used an integrated diffusion-weighted imaging approach for simultaneous assessment of tissue cellularity, vascularity, and heterogeneity – DISMANTLE – to predict molecular subtypes and prognostic factors of breast cancer. We investigated the feasibility of using the histogram features of the cellularity-, vascularity-, and heterogeneity-related parameters of DISMANTLE for differentiation between luminal-A and luminal-B and HER2+ and HER2- breast cancer.

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