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Ultra-low-field brain MRI morphometry : Test–retest reliability and correspondence to high-field MRI

Váša, František ; Bennallick, Carly ; Bourke, Niall J. ; Padormo, Francesco ; Baljer, Levente ; Briski, Ula ; Cawley, Paul ; Arichi, Tomoki ; Wood, Tobias C. and Lythgoe, David J. , et al. (2025) In Imaging Neuroscience 3.
Abstract

Magnetic resonance imaging (MRI) enables non-invasive monitoring of healthy brain development and disease. Widely used higher field (>1.5 T) MRI systems are associated with high energy and infrastructure requirements, and high costs. Recent ultra-low-field (<0.1 T) systems provide a more accessible and cost-effective alternative. However, it remains uncertain whether anatomical ultra-low-field neuroimaging can be used to reliably extract quantitative measures of brain morphometry, and to what extent such measures correspond to high-field MRI. Here we scanned 23 healthy adults aged 20–69 years on two identical 64 mT systems and a 3 T system, using T1w and T2w scans across a range of (64 mT) resolutions. We... (More)

Magnetic resonance imaging (MRI) enables non-invasive monitoring of healthy brain development and disease. Widely used higher field (>1.5 T) MRI systems are associated with high energy and infrastructure requirements, and high costs. Recent ultra-low-field (<0.1 T) systems provide a more accessible and cost-effective alternative. However, it remains uncertain whether anatomical ultra-low-field neuroimaging can be used to reliably extract quantitative measures of brain morphometry, and to what extent such measures correspond to high-field MRI. Here we scanned 23 healthy adults aged 20–69 years on two identical 64 mT systems and a 3 T system, using T1w and T2w scans across a range of (64 mT) resolutions. We segmented brain images into 4 global tissue types and 98 local structures, and systematically evaluated between-scanner reliability of 64 mT morphometry and correspondence to 3 T measurements, using correlations of tissue volume and Dice spatial overlap of segmentations. We report high 64 mT reliability and correspondence to 3 T across 64 mT scan contrasts and resolutions, with highest performance shown by combining three T2w scans with low through-plane resolution into a single higher-resolution scan using multi-resolution registration. Larger structures show higher 64 mT reliability and correspondence to 3 T. Finally, we showcase the potential of ultra-low-field MRI for mapping neuroanatomical changes across the lifespan, and monitoring brain structures relevant to neurological disorders. Raw images are publicly available, enabling systematic validation of pre-processing and analysis approaches for ultra-low-field neuroimaging.

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organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
anatomy, low- and middle-income countries (LMIC), magnetic resonance imaging, morphometry, segmentation, ultra-low-field
in
Imaging Neuroscience
volume
3
article number
IMAG.a.930
publisher
MIT Press
external identifiers
  • scopus:105019065540
  • pmid:41113937
ISSN
2837-6056
DOI
10.1162/IMAG.a.930
language
English
LU publication?
yes
id
7db1b122-de78-44a1-be5e-8f8e0f07ca73
date added to LUP
2025-12-16 14:15:50
date last changed
2025-12-17 03:37:31
@article{7db1b122-de78-44a1-be5e-8f8e0f07ca73,
  abstract     = {{<p>Magnetic resonance imaging (MRI) enables non-invasive monitoring of healthy brain development and disease. Widely used higher field (&gt;1.5 T) MRI systems are associated with high energy and infrastructure requirements, and high costs. Recent ultra-low-field (&lt;0.1 T) systems provide a more accessible and cost-effective alternative. However, it remains uncertain whether anatomical ultra-low-field neuroimaging can be used to reliably extract quantitative measures of brain morphometry, and to what extent such measures correspond to high-field MRI. Here we scanned 23 healthy adults aged 20–69 years on two identical 64 mT systems and a 3 T system, using T<sub>1</sub>w and T<sub>2</sub>w scans across a range of (64 mT) resolutions. We segmented brain images into 4 global tissue types and 98 local structures, and systematically evaluated between-scanner reliability of 64 mT morphometry and correspondence to 3 T measurements, using correlations of tissue volume and Dice spatial overlap of segmentations. We report high 64 mT reliability and correspondence to 3 T across 64 mT scan contrasts and resolutions, with highest performance shown by combining three T<sub>2</sub>w scans with low through-plane resolution into a single higher-resolution scan using multi-resolution registration. Larger structures show higher 64 mT reliability and correspondence to 3 T. Finally, we showcase the potential of ultra-low-field MRI for mapping neuroanatomical changes across the lifespan, and monitoring brain structures relevant to neurological disorders. Raw images are publicly available, enabling systematic validation of pre-processing and analysis approaches for ultra-low-field neuroimaging.</p>}},
  author       = {{Váša, František and Bennallick, Carly and Bourke, Niall J. and Padormo, Francesco and Baljer, Levente and Briski, Ula and Cawley, Paul and Arichi, Tomoki and Wood, Tobias C. and Lythgoe, David J. and Dell’Acqua, Flavio and Booth, Thomas C. and Venkataraman, Ashwin V. and Ljungberg, Emil and Deoni, Sean C.L. and Moran, Rosalyn J. and Leech, Robert and Williams, Steven C.R.}},
  issn         = {{2837-6056}},
  keywords     = {{anatomy; low- and middle-income countries (LMIC); magnetic resonance imaging; morphometry; segmentation; ultra-low-field}},
  language     = {{eng}},
  publisher    = {{MIT Press}},
  series       = {{Imaging Neuroscience}},
  title        = {{Ultra-low-field brain MRI morphometry : Test–retest reliability and correspondence to high-field MRI}},
  url          = {{http://dx.doi.org/10.1162/IMAG.a.930}},
  doi          = {{10.1162/IMAG.a.930}},
  volume       = {{3}},
  year         = {{2025}},
}