Diagnostic performance of ultra-low-field neurological magnetic resonance imaging: a systematic review and meta-analysis
- 1School of Nursing, Midwifery, Allied and Public Health, Canterbury Christ Church University, Canterbury, UK
- 2Radiology, Dartford and Gravesham NHS Trust, Dartford, UK
Abstract
Objectives: To systematically review the reported level of diagnostic performance of ultra-low-field MRI (ULF-MRI) in brain imaging of both paediatrics (including neonates and infants) and adults from a range of neurological conditions.
Design: A systematic literature review used the Population, Index Test, Reference Test, Diagnsotic Outcome (PIRD) framework to identify keywords for electronic database searches to identify studies of ULF-MRI (index test) against standard cross-sectional imaging (reference standard) that presented diagnostic outcome accuracy, with the search documented in a Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) flow chart.
Data sources: A comprehensive literature search was conducted between February and March 2026 in the electronic databases PubMed, Medline, Cumulative Index to Nursing and Allied Health Literature (CINHAL), Embase, Web of Science, Scopus, Cochrane Central Register of Controlled Trials and Google Scholar, without date restriction
Eligibility criteria: Published peer-reviewed primary data studies in English were included, involving human subjects of any age or gender undergoing brain imaging, irrespective of health or clinical indications. Studies were required to have used ULF-MRI, to report diagnostic accuracy or image evaluation and to provide comparative findings with conventional cross-sectional neuroimaging. No restriction on study design, setting, country, patient population or MRI vendor was included. Exclusions included non-brain and non-human imaging, phantom studies, artificial intelligence use or missing diagnostic outcome data.
Data extraction and synthesis: The Quality Assessment of Diagnostic test Accuracy Studies (QUADAS-3) tool was used to assess the quality of retrieved studies. After screening the studies, a meta-analysis for pooled sensitivity, specificity, positive and negative likelihood ratios and diagnostic OR was conducted and expressed in forest plots, pooled heterogeneity values, 95% CIs, probability values and summary receiver operating characteristic curve plotted for area under the curve (AUC).
Results: In total, n=17 studies were identified for pooled meta-analysis; n=9 compared ULF-MRI directly to conventional MRI, and n=8 compared it to a mix of conventional MRI and CT. Wide variability in methodology was identified across pilot and observational studies, with imaging sample sizes ranging from n=8 to n=189, readers n=1–2 and neurological conditions assessed, which affected the risk of bias and warranted caution in interpreting meta-analysis results. Overall sensitivity was 90% (95% CI 0.82 to 0.94); specificity was 98% (95% CI 0.97 to 0.99); AUC was 0.99, with significant heterogeneity (χ2=39.77; p=0.008; I2=59.8%) between studies.
Conclusion: Significant heterogeneity in study methodologies was identified, warranting caution when interpreting the meta-analysis results. The studies demonstrated high diagnostic performance for gross structural neurological conditions, but detecting small, subtle lesions below 6 mm was problematic with ULF-MRI. However, ULF-MRI is not positioned in the studies as a replacement for conventional MRI, but rather as a complementary tool for monitoring, triage and imaging follow-up during bedside assessment, particularly in critical patient environments.
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BibTeX
@article{lockwood2026diagnostic,
title = {{Diagnostic performance of ultra-low-field neurological magnetic resonance imaging: a systematic review and meta-analysis}},
author = {Paul Lockwood and Elizabeth Barrett},
journal = {BMJ Open},
year = {2026},
month = oct,
doi = {10.1136/bmjopen-2026-124306},
url = {https://bmjopen.bmj.com/lookup/doi/10.1136/bmjopen-2026-124306},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - Diagnostic performance of ultra-low-field neurological magnetic resonance imaging: a systematic review and meta-analysis
AU - Paul Lockwood
AU - Elizabeth Barrett
PY - 2026
DA - 2026/10/30
JO - BMJ Open
DO - 10.1136/bmjopen-2026-124306
UR - https://bmjopen.bmj.com/lookup/doi/10.1136/bmjopen-2026-124306
AB - Objectives: To systematically review the reported level of diagnostic performance of ultra-low-field MRI (ULF-MRI) in brain imaging of both paediatrics (including neonates and infants) and adults from a range of neurological conditions. Design: A systematic literature review used the Population, Index Test, Reference Test, Diagnsotic Outcome (PIRD) framework to identify keywords for electronic database searches to identify studies of ULF-MRI (index test) against standard cross-sectional imaging (reference standard) that presented diagnostic outcome accuracy, with the search documented in a Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) flow chart. Data sources: A comprehensive literature search was conducted between February and March 2026 in the electronic databases PubMed, Medline, Cumulative Index to Nursing and Allied Health Literature (CINHAL), Embase, Web of Science, Scopus, Cochrane Central Register of Controlled Trials and Google Scholar, without date restriction Eligibility criteria: Published peer-reviewed primary data studies in English were included, involving human subjects of any age or gender undergoing brain imaging, irrespective of health or clinical indications. Studies were required to have used ULF-MRI, to report diagnostic accuracy or image evaluation and to provide comparative findings with conventional cross-sectional neuroimaging. No restriction on study design, setting, country, patient population or MRI vendor was included. Exclusions included non-brain and non-human imaging, phantom studies, artificial intelligence use or missing diagnostic outcome data. Data extraction and synthesis: The Quality Assessment of Diagnostic test Accuracy Studies (QUADAS-3) tool was used to assess the quality of retrieved studies. After screening the studies, a meta-analysis for pooled sensitivity, specificity, positive and negative likelihood ratios and diagnostic OR was conducted and expressed in forest plots, pooled heterogeneity values, 95% CIs, probability values and summary receiver operating characteristic curve plotted for area under the curve (AUC). Results: In total, n=17 studies were identified for pooled meta-analysis; n=9 compared ULF-MRI directly to conventional MRI, and n=8 compared it to a mix of conventional MRI and CT. Wide variability in methodology was identified across pilot and observational studies, with imaging sample sizes ranging from n=8 to n=189, readers n=1–2 and neurological conditions assessed, which affected the risk of bias and warranted caution in interpreting meta-analysis results. Overall sensitivity was 90% (95% CI 0.82 to 0.94); specificity was 98% (95% CI 0.97 to 0.99); AUC was 0.99, with significant heterogeneity (χ2=39.77; p=0.008; I2=59.8%) between studies. Conclusion: Significant heterogeneity in study methodologies was identified, warranting caution when interpreting the meta-analysis results. The studies demonstrated high diagnostic performance for gross structural neurological conditions, but detecting small, subtle lesions below 6 mm was problematic with ULF-MRI. However, ULF-MRI is not positioned in the studies as a replacement for conventional MRI, but rather as a complementary tool for monitoring, triage and imaging follow-up during bedside assessment, particularly in critical patient environments.
SN - 2044-6055
SN - 2044-6055
ER -