Abstract #1187

Jointly Reconstructed Undersampled Multiparameter MRI for Imaging Intratumoral Subpopulations

Shraddha Pandey^1,2, Arthur David Snider¹, Wilfrido Moreno¹, Harshan Ravi², Ali Bilgin³, and Natarajan Raghunand^2,4

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].

This abstract and the presentation materials are available to members only; a login is required.

Join Here