Best fast MRI protocols for the knee: advantages and limitations

Nacey NC, et al. Magnetic resonance imaging of the knee: an overview and update of conventional and state of the art imaging. J Magn Reson Imaging. 2017;45(5):1257–75.

Article  PubMed  Google Scholar 

Lin DJ, Walter SS, Fritz J. Artificial intelligence-driven ultra-fast superresolution MRI: 10-fold accelerated musculoskeletal turbo spin echo MRI within reach. Invest Radiol. 2023;58(1):28–42.

Article  PubMed  Google Scholar 

Barth M, et al. Simultaneous multislice (SMS) imaging techniques. Magn Reson Med. 2016;75(1):63–81.

Article  PubMed  Google Scholar 

Deshmane A, et al. Parallel MR imaging. J Magn Reson Imaging. 2012;36(1):55–72.

Article  PubMed  PubMed Central  Google Scholar 

Lustig M, Donoho D, Pauly JM. Sparse MRI: the application of compressed sensing for rapid MR imaging. Magn Reson Med. 2007;58(6):1182–95.

Article  PubMed  Google Scholar 

Fritz J, Kijowski R, Recht MP. Artificial intelligence in musculoskeletal imaging: a perspective on value propositions, clinical use, and obstacles. Skeletal Radiol. 2022;51(2):239–43.

Article  PubMed  Google Scholar 

Vosshenrich J, Koerzdoerfer G, Fritz J. Modern acceleration in musculoskeletal MRI: applications, implications, and challenges. Skeletal Radiol. 2024;53(9):1799–813.

Article  PubMed  Google Scholar 

Del Grande F, Guggenberger R, Fritz J. Rapid musculoskeletal MRI in 2021: value and optimized use of widely accessible techniques. AJR Am J Roentgenol. 2021;216(3):704–17.

Article  PubMed  Google Scholar 

Garwood ER, Recht MP, White LM. Advanced imaging techniques in the knee: benefits and limitations of new rapid acquisition strategies for routine knee MRI. AJR Am J Roentgenol. 2017;209(3):552–60.

Article  PubMed  Google Scholar 

Breuer FA, et al. General formulation for quantitative G-factor calculation in GRAPPA reconstructions. Magn Reson Med. 2009;62(3):739–46.

Article  PubMed  Google Scholar 

Larkman DJ, et al. Use of multicoil arrays for separation of signal from multiple slices simultaneously excited. J Magn Reson Imaging. 2001;13(2):313–7.

Article  CAS  PubMed  Google Scholar 

Fritz J, Guggenberger R, Grande FD. Rapid musculoskeletal MRI in 2021: clinical application of advanced accelerated techniques. AJR Am J Roentgenol. 2021;216(3):718–33.

Article  PubMed  Google Scholar 

Fritz J, et al. Simultaneous multislice accelerated turbo spin echo magnetic resonance imaging: comparison and combination with in-plane parallel imaging acceleration for high-resolution magnetic resonance imaging of the knee. Invest Radiol. 2017;52(9):529–37.

Article  CAS  PubMed  Google Scholar 

Li X, et al. Is simultaneous multisection turbo spin echo ready for clinical MRI? A feasibility study on fast imaging of knee lesions. Clin Radiol. 2020;75(3):238.e21-238.e30.

Article  CAS  PubMed  Google Scholar 

Yang AC, et al. Sparse reconstruction techniques in magnetic resonance imaging: methods, applications, and challenges to clinical adoption. Invest Radiol. 2016;51(6):349–64.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Geethanath S, et al. Compressed sensing MRI: a review. Crit Rev Biomed Eng. 2013;41(3):183–204.

Article  PubMed  Google Scholar 

Kijowski R, et al. Knee imaging: rapid three-dimensional fast spin-echo using compressed sensing. J Magn Reson Imaging. 2017;45(6):1712–22.

Article  PubMed  Google Scholar 

Matcuk GR, et al. Compressed sensing MR imaging (CS-MRI) of the knee: assessment of quality, inter-reader agreement, and acquisition time. Magn Reson Med Sci. 2020;19(3):254–8.

Article  PubMed  Google Scholar 

Otazo R, et al. Sparse-SEMAC: rapid and improved SEMAC metal implant imaging using SPARSE-SENSE acceleration. Magn Reson Med. 2017;78(1):79–87.

Article  CAS  PubMed  Google Scholar 

Fritz J, et al. Compressed sensing SEMAC: 8-fold accelerated high resolution metal artifact reduction MRI of cobalt-chromium knee arthroplasty implants. Invest Radiol. 2016;51(10):666–76.

Article  CAS  PubMed  Google Scholar 

Del Grande F, et al. Five-minute five-sequence knee MRI using combined simultaneous multislice and parallel imaging acceleration: comparison with 10-minute parallel imaging knee MRI. Radiology. 2021;299(3):635–46.

Article  PubMed  Google Scholar 

Kijowski R, Fritz J. Emerging technology in musculoskeletal MRI and CT. Radiology. 2023;306(1):6–19.

Article  PubMed  Google Scholar 

Wang S, et al. Accelerating magnetic resonance imaging via deep learning. Proc IEEE Int Symp Biomed Imaging. 2016;2016:514–7.

PubMed  PubMed Central  Google Scholar 

Chaudhari AS, et al. Super-resolution musculoskeletal MRI using deep learning. Magn Reson Med. 2018;80(5):2139–54.

Article  PubMed  PubMed Central  Google Scholar 

Knoll F, et al. Advancing machine learning for MR image reconstruction with an open competition: overview of the 2019 fastMRI challenge. Magn Reson Med. 2020;84(6):3054–70.

Article  PubMed  PubMed Central  Google Scholar 

Recht MP, et al. Using deep learning to accelerate knee MRI at 3 T: results of an interchangeability study. AJR Am J Roentgenol. 2020;215(6):1421–9.

Article  PubMed  PubMed Central  Google Scholar 

Johnson PM, et al. Deep learning reconstruction enables prospectively accelerated clinical knee MRI. Radiology. 2023;307(2):e220425.

Article  PubMed  PubMed Central  Google Scholar 

Walter SS, et al. Deep learning superresolution for simultaneous multislice parallel imaging-accelerated knee MRI using arthroscopy validation. Radiology. 2025;314(1):e241249.

Article  PubMed  Google Scholar 

Vosshenrich J, et al. Arthroscopy-validated diagnostic performance of sub-5-min deep learning super-resolution 3T knee MRI in children and adolescents. Skeletal Radiol. 2025;54(12):2705–16.

Article  PubMed  Google Scholar 

Vosshenrich J, et al. Clinical implementation of sixfold-accelerated deep learning super-resolution knee MRI in under 5 minutes: arthroscopy-validated diagnostic performance. AJR Am J Roentgenol. 2025. https://doi.org/10.2214/AJR.25.32878.

Article  PubMed  Google Scholar 

Vosshenrich J, et al. Arthroscopy-validated diagnostic performance of 7-minute five-sequence deep learning super-resolution 3-T shoulder MRI. Radiology. 2025;314(2):e241351.

Article  PubMed  Google Scholar 

Herrmann J, et al. Feasibility and implementation of a deep learning MR reconstruction for TSE sequences in musculoskeletal imaging. Diagnostics. 2021. https://doi.org/10.3390/diagnostics11081484.

Almansour H, et al. Deep learning reconstruction for accelerated spine MRI: prospective analysis of interchangeability. Radiology. 2022;306(3):e212922.

Article  PubMed  Google Scholar 

Hahn S, et al. Comparison of deep learning-based reconstruction of PROPELLER shoulder MRI with conventional reconstruction. Skeletal Radiol. 2023;52(8):1545–55.

Article  PubMed  Google Scholar 

Hahn S, et al. Image quality and diagnostic performance of accelerated shoulder MRI with deep learning-based reconstruction. AJR Am J Roentgenol. 2022;218(3):506–16.

Article  PubMed  Google Scholar 

R. Marc Lebel, P. Performance characterization of a novel deep learning-based MR image reconstruction pipeline.ArXiv, 2020. abs/2008.06559.

Kaniewska M, et al. Deep learning convolutional neural network reconstruction and radial k-space acquisition MR technique for enhanced detection of retropatellar cartilage lesions of the knee joint. Diagnostics. 2023. https://doi.org/10.3390/diagnostics13142438.

Comments (0)

No login
gif