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Abstract #3966

High-resolution Diffusion Tensor Imaging at 7T with Multi-band Multi-shot EPI acquisition and Deep Learning Reconstruction

Xinzeng Wang1, Baolian Yang2, Marc R. Label3, Steen Moeller4, and Suchandrima Banerjee5
1GE Healthcare, Houston, TX, United States, 2GE Healthcare, Waukesha, WI, United States, 3GE Healthcare, Calgary, AB, Canada, 4Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, MN, United States, 5GE Healthcare, Menlo Park, CA, United States


Diffusion tensor imaging (DTI) is a well-established tool for providing insights into brain network connectivity and detecting brain microstructure but suffers from artifacts, low SNR, low spatial resolution, and long scan times. High-resolution DTI at 7T with multiband MUSE (MB-MUSE) and noise reduction methods have shown many potentials for mitigating these challenges. In this study, we combine a deep learning reconstruction method with MB-MUSE to overcome the image quality challenges and demonstrate improved quantification of high-resolution DTI at 7T compared with MB-MUSE and MB-MUSE with low-rank denoising.

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