Deep Learning Based Reconstruction for Multi-shot DWI of the Breast: A Preliminary Study

Diffusion-weighted imaging (DWI) in the breast is limited by image distortion, which can be improved with multi-shot DWI (MUSE). We conducted a pilot study to investigate the impact of deep-learning reconstruction (DLRecon) on MUSE image quality. Compared with the non-DL MUSE images, the MUSE DLRecon showed higher SNR without altering the mean ADC value. Moreover, the higher shots MUSE DL with reduced NEX could provide less-distortion DWI with comparable SNR and scan time to 2-shot MUSE imaging, which is commonly used in the clinical setting. Preliminary results indicate the feasibility of MUSE-DWI in the breast with higher number of shots.