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Abstract #1187

Jointly Reconstructed Undersampled Multiparameter MRI for Imaging Intratumoral Subpopulations

Shraddha Pandey1,2, Arthur David Snider1, Wilfrido Moreno1, Harshan Ravi2, Ali Bilgin3, and Natarajan Raghunand2,4
1Electrical Engineering, University of South Florida, Tampa, FL, United States, 2Cancer Physiology, Moffitt Cancer Center, Tampa, FL, United States, 3Departments of Medical Imaging, Biomedical Engineering, and Electrical & Computer Engineering, University of Arizona, Tucson, AZ, United States, 4Department of Oncologic Sciences, University of South Florida, Tampa, FL, United States

A joint reconstruction framework is proposed to reconstruct a series of T1-weighted, T2-weighted, and T2*-weighted images and corresponding parameter maps simultaneously from undersampled cartesian k-space data. Joint Total Variation (JTV) and model-based constraints were employed to resolve the ambiguity introduced due to undersampling. T1 and T2 maps were used to identify fluid, adipose, muscle and tumor tissue types. T2*w images reconstructed from undersampled data were analyzed to produce maps of Proton Density Fat Fraction (PDFF), Proton Density Water Fraction (PDwF), and the relaxation rates of water ($$$R^*_{2w}$$$) and fat ($$$R^*_{2f}$$$) in each tissue type [1].

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