Rapid Multiparametric Quantitative Bilateral Breast MR Fingerprinting Using a Phase-Sensitive Deep Learning Network.

Motivation: To rapidly obtain MRF-based multiparametric quantitative maps in the breast. Goal(s): To explore the feasibility of using PS-DRONE and an EPI-MRF sequence in breast imaging to simultaneously quantify T1, T2, PD, B1, phase, and QSM maps. Approach: MRF data were acquired at 3T. Tissue parameters were reconstructed using PS-DRONE, including QSM maps computed from the estimated phase. Results: Bilateral breast T1, T2, PD, B1 and phase (for QSM analysis) maps were obtained using PS-DRONE and an EPI-MRF sequence. Scan time was 2 minutes and 30 seconds. Parameter reconstruction time was one second. Maps presented differences between the two breasts consistent with diffusion images. Impact: Comprehensive quantitative T1, T2, PD, B1 and phase (QSM) bilateral breast imaging in under 2.5 minutes can potentially improve the detection and characterization of breast cancer and treatment response in a clinical setting without the use of a contrast agent.