Affiliation:
1. Department of Radiology Stanford University Stanford California USA
2. Department of Radiology and Research Institute of Radiology University of Ulsan College of Medicine, Asan Medical Center Seoul South Korea
3. Department of Orthopaedic Surgery Stanford University Stanford California USA
4. Department of Bioengineering Stanford University Stanford California USA
Abstract
With a substantial growth in the use of musculoskeletal MRI, there has been a growing need to improve MRI workflow, and faster imaging has been suggested as one of the solutions for a more efficient examination process. Consequently, there have been considerable advances in accelerated MRI scanning methods. This article aims to review the basic principles and applications of accelerated musculoskeletal MRI techniques including widely used conventional acceleration methods, more advanced deep learning‐based techniques, and new approaches to reduce scan time. Specifically, conventional accelerated MRI techniques, including parallel imaging, compressed sensing, and simultaneous multislice imaging, and deep learning‐based accelerated MRI techniques, including undersampled MR image reconstruction, super‐resolution imaging, artifact correction, and generation of unacquired contrast images, are discussed. Finally, new approaches to reduce scan time, including synthetic MRI, novel sequences, and new coil setups and designs, are also reviewed. We believe that a deep understanding of these fast MRI techniques and proper use of combined acceleration methods will synergistically improve scan time and MRI workflow in daily practice.Evidence Level3Technical EfficacyStage 1
Subject
Radiology, Nuclear Medicine and imaging