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Kimberly WT, Sorby-Adams AJ, Webb AG, Wu EX, Beekman R, Bowry R, Schiff SJ, de Havenon A, Shen FX, Sze G, Schaefer P, Iglesias JE, Rosen MS, Sheth KN. Brain imaging with portable low-field MRI. NATURE REVIEWS BIOENGINEERING 2023; 1:617-630. [PMID: 37705717 PMCID: PMC10497072 DOI: 10.1038/s44222-023-00086-w] [Citation(s) in RCA: 16] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 06/06/2023] [Indexed: 09/15/2023]
Abstract
The advent of portable, low-field MRI (LF-MRI) heralds new opportunities in neuroimaging. Low power requirements and transportability have enabled scanning outside the controlled environment of a conventional MRI suite, enhancing access to neuroimaging for indications that are not well suited to existing technologies. Maximizing the information extracted from the reduced signal-to-noise ratio of LF-MRI is crucial to developing clinically useful diagnostic images. Progress in electromagnetic noise cancellation and machine learning reconstruction algorithms from sparse k-space data as well as new approaches to image enhancement have now enabled these advancements. Coupling technological innovation with bedside imaging creates new prospects in visualizing the healthy brain and detecting acute and chronic pathological changes. Ongoing development of hardware, improvements in pulse sequences and image reconstruction, and validation of clinical utility will continue to accelerate this field. As further innovation occurs, portable LF-MRI will facilitate the democratization of MRI and create new applications not previously feasible with conventional systems.
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Affiliation(s)
- W Taylor Kimberly
- Department of Neurology and the Center for Genomic Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Annabel J Sorby-Adams
- Department of Neurology and the Center for Genomic Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Andrew G Webb
- Department of Radiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Ed X Wu
- Laboratory of Biomedical Imaging and Signal Processing, Department of Electrical and Electronic Engineering, The University of Hong Kong, Hong Kong SAR, China
| | - Rachel Beekman
- Division of Neurocritical Care and Emergency Neurology, Department of Neurology, Yale New Haven Hospital and Yale School of Medicine, Yale Center for Brain & Mind Health, New Haven, CT, USA
| | - Ritvij Bowry
- Departments of Neurosurgery and Neurology, McGovern Medical School, University of Texas Health Neurosciences, Houston, TX, USA
| | - Steven J Schiff
- Department of Neurosurgery, Yale School of Medicine, New Haven, CT, USA
| | - Adam de Havenon
- Division of Vascular Neurology, Department of Neurology, Yale New Haven Hospital and Yale School of Medicine, New Haven, CT, USA
| | - Francis X Shen
- Harvard Medical School Center for Bioethics, Harvard law School, Boston, MA, USA
- Department of Psychiatry, Massachusetts General Hospital, Boston, MA, USA
| | - Gordon Sze
- Department of Radiology, Yale New Haven Hospital and Yale School of Medicine, New Haven, CT, USA
| | - Pamela Schaefer
- Division of Neuroradiology, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Juan Eugenio Iglesias
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
- Centre for Medical Image Computing, University College London, London, UK
- Computer Science and AI Laboratory, Massachusetts Institute of Technology, Boston, MA, USA
| | - Matthew S Rosen
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Kevin N Sheth
- Division of Neurocritical Care and Emergency Neurology, Department of Neurology, Yale New Haven Hospital and Yale School of Medicine, Yale Center for Brain & Mind Health, New Haven, CT, USA
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Froelich T, DelaBarre L, Wang P, Radder J, Torres E, Garwood M. Fast spin-echo approach for accelerated B 1 gradient-based MRI. Magn Reson Med 2023; 89:2204-2216. [PMID: 36669882 PMCID: PMC10050123 DOI: 10.1002/mrm.29592] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2022] [Revised: 12/06/2022] [Accepted: 01/05/2023] [Indexed: 01/22/2023]
Abstract
PURPOSE To expand on the previously developedB 1 + $$ {\mathrm{B}}_1^{+} $$ -encoding technique, frequency-modulated Rabi-encoded echoes (FREE), to perform accelerated image acquisition by collecting multiple lines of k-space in an echo train. METHODS FREE uses adiabatic full-passage pulses and a spatially varying RF field to encode unique spatial information without the use of traditional B0 gradients. The original implementation relied on acquiring single lines of k-space, leading to long acquisitions. In this work, an acceleration scheme is presented in which multiple echoes are acquired in a single shot, analogous to conventional fast spin-echo sequences. Theoretical analysis and computer simulations investigated the feasibility of this approach and presented a framework to analyze important imaging parameters of FREE-based sequences. Experimentally, the multi-echo approach was compared with conventional phase-encoded images of the human visual cortex using a simple surface transceiver coil. Finally, different contrasts demonstrated the clinical versatility of the new accelerated sequence. RESULTS Images were acquired with an acceleration factor of 3.9, compared with the previous implementation of FREE, without exceeding specific absorption rate limits. Different contrasts can easily be acquired without major modifications, including inversion recovery-type images. CONCLUSION FREE initially illustrated the feasibility of performing slice-selective 2D imaging of the human brain without the need for a B0 gradient along the y-direction. The multi-echo version maintains the advantages thatB 1 + $$ {\mathrm{B}}_1^{+} $$ encoding provides but represents an important step toward improving the clinical feasibility of such sequences. Additional acceleration and more advanced reconstruction techniques could further improve the clinical viability of FREE-based techniques.
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Affiliation(s)
- Taylor Froelich
- Center for Magnetic Resonance Research and Department of Radiology, University of Minnesota, Minneapolis, Minnesota, USA
| | - Lance DelaBarre
- Center for Magnetic Resonance Research and Department of Radiology, University of Minnesota, Minneapolis, Minnesota, USA
| | - Paul Wang
- Center for Magnetic Resonance Research and Department of Radiology, University of Minnesota, Minneapolis, Minnesota, USA
- Department of Biomedical Engineering, University of Minnesota, Minneapolis, Minnesota, USA
| | - Jerahmie Radder
- Center for Magnetic Resonance Research and Department of Radiology, University of Minnesota, Minneapolis, Minnesota, USA
| | - Efraín Torres
- Center for Magnetic Resonance Research and Department of Radiology, University of Minnesota, Minneapolis, Minnesota, USA
- Department of Biomedical Engineering, University of Minnesota, Minneapolis, Minnesota, USA
| | - Michael Garwood
- Center for Magnetic Resonance Research and Department of Radiology, University of Minnesota, Minneapolis, Minnesota, USA
- Department of Biomedical Engineering, University of Minnesota, Minneapolis, Minnesota, USA
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