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

Emil Ljungberg; Francesco Padormo; Megan Poorman; Petter Clemensson; Niall Bourke; John C Evans; James Gholam; Irene Vavasour; Shannon H Kollind; Samson L Lafayette; Carly Bennallick; Kirsten A Donald; Layla E Bradford; Beatrice Lena; Maclean Vokhiwa; Talat Shama; Jasmine Siew; Lydia Sekoli; Jeanne van Rensburg; Michael S Pepper; Amna Khan; Akber Madhwani; Frank A Banda; Mwila L Mwila; Adam R Cassidy; Kebaiphe Moabi; Dolly Sephi; Richard A Boakye; Kenneth A Ae-Ngibise; Kwaku P Asante; William J Hollander; Todor Karaulanov; Steven C R Williams; Sean Deoni

doi:10.1002/hbm.70217

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

Emil Ljungberg, Francesco Padormo, Megan Poorman, Petter Clemensson, Niall Bourke, John C Evans, James Gholam, Irene Vavasour, Shannon H Kollind, Samson L Lafayette, Carly Bennallick, Kirsten A Donald, Layla E Bradford, Beatrice Lena, Maclean Vokhiwa, Talat Shama, Jasmine Siew, Lydia Sekoli, Jeanne van Rensburg, Michael S PepperAmna Khan, Akber Madhwani, Frank A Banda, Mwila L Mwila, Adam R Cassidy, Kebaiphe Moabi, Dolly Sephi, Richard A Boakye, Kenneth A Ae-Ngibise, Kwaku P Asante, William J Hollander, Todor Karaulanov, Steven C R Williams, Sean Deoni

Research output: Contribution to journal › Article › peer-review

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.

Original language	English
Article number	e70217
Pages (from-to)	e70217
Journal	Human Brain Mapping
Volume	46
Issue number	8
Early online date	23 May 2025
DOIs	https://doi.org/10.1002/hbm.70217
Publication status	Published - 1 Jun 2025

Keywords

Magnetic Resonance Imaging/instrumentation
Humans
Neuroimaging/instrumentation
Phantoms, Imaging
Brain/diagnostic imaging
Quality Control
Image Processing, Computer-Assisted
Signal-To-Noise Ratio

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10.1002/hbm.70217

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Ljungberg, E., Padormo, F., Poorman, M., Clemensson, P., Bourke, N., Evans, J. C., Gholam, J., Vavasour, I., Kollind, S. H., Lafayette, S. L., Bennallick, C., Donald, K. A., Bradford, L. E., Lena, B., Vokhiwa, M., Shama, T., Siew, J., Sekoli, L., van Rensburg, J., ... Deoni, S. (2025). Characterization of Portable Ultra-Low Field MRI Scanners for Multi-Center Structural Neuroimaging. Human Brain Mapping, 46(8), e70217. Article e70217. https://doi.org/10.1002/hbm.70217

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title = "Characterization of Portable Ultra-Low Field MRI Scanners for Multi-Center Structural Neuroimaging",

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.",

keywords = "Magnetic Resonance Imaging/instrumentation, Humans, Neuroimaging/instrumentation, Phantoms, Imaging, Brain/diagnostic imaging, Quality Control, Image Processing, Computer-Assisted, Signal-To-Noise Ratio",

author = "Emil Ljungberg and Francesco Padormo and Megan Poorman and Petter Clemensson and Niall Bourke and Evans, {John C} and James Gholam and Irene Vavasour and Kollind, {Shannon H} and Lafayette, {Samson L} and Carly Bennallick and Donald, {Kirsten A} and Bradford, {Layla E} and Beatrice Lena and Maclean Vokhiwa and Talat Shama and Jasmine Siew and Lydia Sekoli and {van Rensburg}, Jeanne and Pepper, {Michael S} and Amna Khan and Akber Madhwani and Banda, {Frank A} and Mwila, {Mwila L} and Cassidy, {Adam R} and Kebaiphe Moabi and Dolly Sephi and Boakye, {Richard A} and Ae-Ngibise, {Kenneth A} and Asante, {Kwaku P} and Hollander, {William J} and Todor Karaulanov and Williams, {Steven C R} and Sean Deoni",

note = "Publisher Copyright: {\textcopyright} 2025 The Author(s). Human Brain Mapping published by Wiley Periodicals LLC.",

year = "2025",

month = jun,

day = "1",

doi = "10.1002/hbm.70217",

language = "English",

volume = "46",

pages = "e70217",

journal = "Human Brain Mapping",

issn = "1065-9471",

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Ljungberg, E, Padormo, F, Poorman, M, Clemensson, P, Bourke, N, Evans, JC, Gholam, J, Vavasour, I, Kollind, SH, Lafayette, SL, Bennallick, C, Donald, KA, Bradford, LE, Lena, B, Vokhiwa, M, Shama, T, Siew, J, Sekoli, L, van Rensburg, J, Pepper, MS, Khan, A, Madhwani, A, Banda, FA, Mwila, ML, Cassidy, AR, Moabi, K, Sephi, D, Boakye, RA, Ae-Ngibise, KA, Asante, KP, Hollander, WJ, Karaulanov, T, Williams, SCR & Deoni, S 2025, 'Characterization of Portable Ultra-Low Field MRI Scanners for Multi-Center Structural Neuroimaging', Human Brain Mapping, vol. 46, no. 8, e70217, pp. e70217. https://doi.org/10.1002/hbm.70217

TY - JOUR

T1 - Characterization of Portable Ultra-Low Field MRI Scanners for Multi-Center Structural Neuroimaging

AU - Ljungberg, Emil

AU - Padormo, Francesco

AU - Poorman, Megan

AU - Clemensson, Petter

AU - Bourke, Niall

AU - Evans, John C

AU - Gholam, James

AU - Vavasour, Irene

AU - Kollind, Shannon H

AU - Lafayette, Samson L

AU - Bennallick, Carly

AU - Donald, Kirsten A

AU - Bradford, Layla E

AU - Lena, Beatrice

AU - Vokhiwa, Maclean

AU - Shama, Talat

AU - Siew, Jasmine

AU - Sekoli, Lydia

AU - van Rensburg, Jeanne

AU - Pepper, Michael S

AU - Khan, Amna

AU - Madhwani, Akber

AU - Banda, Frank A

AU - Mwila, Mwila L

AU - Cassidy, Adam R

AU - Moabi, Kebaiphe

AU - Sephi, Dolly

AU - Boakye, Richard A

AU - Ae-Ngibise, Kenneth A

AU - Asante, Kwaku P

AU - Hollander, William J

AU - Karaulanov, Todor

AU - Williams, Steven C R

AU - Deoni, Sean

PY - 2025/6/1

Y1 - 2025/6/1

N2 - 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.

AB - 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.

KW - Magnetic Resonance Imaging/instrumentation

KW - Humans

KW - Neuroimaging/instrumentation

KW - Phantoms, Imaging

KW - Brain/diagnostic imaging

KW - Quality Control

KW - Image Processing, Computer-Assisted

KW - Signal-To-Noise Ratio

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U2 - 10.1002/hbm.70217

DO - 10.1002/hbm.70217

M3 - Article

C2 - 40405769

SN - 1065-9471

VL - 46

SP - e70217

JO - Human Brain Mapping

JF - Human Brain Mapping

IS - 8

M1 - e70217

ER -

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

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Keywords

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