Characterization of Portable Ultra‐Low Field <scp>MRI</scp> Scanners for Multi‐Center Structural Neuroimaging

The lower infrastructure requirements of portable ultra-low field MRI (ULF-MRI) systems have enabled their use in diverse settings such as intensive care units and remote medical facilities. The UNITY Project is an international neuroimaging network harnessing this technology, deploying portable ULF-MRI systems globally to expand access to MRI for studies into brain development. Given the wide range of environments where ULF-MRI systems may operate, there are external factors that might influence image quality. This work aims to introduce the quality control (QC) framework used by the UNITY Project to investigate how robust the systems are and how QC metrics compare between sites and over time. We present a QC framework using a commercially available phantom, scanned with 64 mT portable MRI systems at 17 sites across 12 countries on four continents. Using automated, open-source analysis tools, we quantify signal-to-noise, image contrast, and geometric distortions. Our results demonstrated that the image quality is robust to the varying operational environment, for example, electromagnetic noise interference and temperature. The Larmor frequency was significantly correlated to room temperature, as was image noise and contrast. Image distortions were less than 2.5 mm, with high robustness over time. Similar to studies at higher field, we found that changes in pulse sequence parameters from software updates had an impact on QC metrics. This study demonstrates that portable ULF-MRI systems can be deployed in a variety of environments for multi-center neuroimaging studies and produce robust results.

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Publication Details

Journal
Human Brain Mapping
Published
2025-05-23
DOI
https://doi.org/10.1002/hbm.70217
Citations
2
Primary Topic
Advanced MRI Techniques and Applications
Type
article
Field-Weighted Citation Impact
2.72

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Characterization of Portable Ultra‐Low Field MRI Scanners for Multi‐Center Structural Neuroimaging

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Advanced MRI Techniques and Applications
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Characterization of Portable Ultra‐Low Field MRI Scanners for Multi‐Center Structural Neuroimaging

Talat Shama, Beatrice Lena, Niall Bourke, Todor Karaulanov, John Evans, Michael S. Pepper, Shannon Kolind, Amna Khan, Adam R. Cassidy, Maclean Vokhiwa, Kebaiphe Moabi, Irene M. Vavasour, Carly Bennallick, Samson Lecurieux Lafayette, Kwaku Poku Asante, Steven Williams, Jasmine Siew, James Gholam, Megan Poorman, Francesco Padormo, Emil Ljungberg, Fareda Banda, Kirsten A. Donald, Janse van Rensburg, Kenneth Ayuurebobi Ae-Ngibise, Akber Madhwani, Sean Deoni, Lydia Sekoli, Layla E. Bradford, W. den Hollander, Petter Clemensson, Mwila L. Mwila, Dolly Sephi, Richard A. Boakye
article en
2 citations

Abstract

The lower infrastructure requirements of portable ultra-low field MRI (ULF-MRI) systems have enabled their use in diverse settings such as intensive care units and remote medical facilities. The UNITY Project is an international neuroimaging network harnessing this technology, deploying portable ULF-MRI systems globally to expand access to MRI for studies into brain development. Given the wide range of environments where ULF-MRI systems may operate, there are external factors that might influence image quality. This work aims to introduce the quality control (QC) framework used by the UNITY Project to investigate how robust the systems are and how QC metrics compare between sites and over time. We present a QC framework using a commercially available phantom, scanned with 64 mT portable MRI systems at 17 sites across 12 countries on four continents. Using automated, open-source analysis tools, we quantify signal-to-noise, image contrast, and geometric distortions. Our results demonstrated that the image quality is robust to the varying operational environment, for example, electromagnetic noise interference and temperature. The Larmor frequency was significantly correlated to room temperature, as was image noise and contrast. Image distortions were less than 2.5 mm, with high robustness over time. Similar to studies at higher field, we found that changes in pulse sequence parameters from software updates had an impact on QC metrics. This study demonstrates that portable ULF-MRI systems can be deployed in a variety of environments for multi-center neuroimaging studies and produce robust results.

Human Brain MappingVol. 46(8)
Aga Khan University (PK), Leiden University (NL), Boston Children's Hospital (US), Gates Foundation (US), Mayo Clinic (US), University of British Columbia (CA), University of Malawi (MW), University of Cape Town (ZA), King's College London (GB), Lund University (SE), International Centre for Diarrhoeal Disease Research (BD), University of Lusaka (ZM), Leiden University Medical Center (NL), University of Colorado System (US), WinnMed (US), University of Zambia (ZM), King's College School (GB), Mayo Clinic in Florida (US), Botswana Harvard AIDS Institute Partnership (BW), Kintampo Health Research Centre (GH), Red Cross War Memorial Children's Hospital (ZA), Guilford College (US), University of Pretoria (ZA), Cardiff University (GB)
Bill and Melinda Gates Foundation, National Institute for Health and Care Research, South African Medical Research Council, Lunds Universitet, NIHR Maudsley Biomedical Research Centre, Medical Research Council
Industry, innovation and infrastructure
Openalex Percentile: Top 11%
Advanced MRI Techniques and Applications
2.72
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