Characterizing T1 in the fetal brain and placenta over gestational age at 0.55T.

fetal MRI low cost low‐field relaxometry

Journal

Magnetic resonance in medicine
ISSN: 1522-2594
Titre abrégé: Magn Reson Med
Pays: United States
ID NLM: 8505245

Informations de publication

Date de publication:
05 Jul 2024
Historique:
revised: 10 05 2024
received: 23 02 2024
accepted: 24 05 2024
medline: 5 7 2024
pubmed: 5 7 2024
entrez: 5 7 2024
Statut: aheadofprint

Résumé

T1 mapping and T1-weighted contrasts have a complimentary but currently under utilized role in fetal MRI. Emerging clinical low field scanners are ideally suited for fetal T1 mapping. The advantages are lower T1 values which results in higher efficiency and reduced field inhomogeneities resulting in a decreased requirement for specialist tools. In addition the increased bore size associated with low field scanners provides improved patient comfort and accessibility. This study aims to demonstrate the feasibility of fetal brain T1 mapping at 0.55T. An efficient slice-shuffling inversion-recovery echo-planar imaging (EPI)-based T1-mapping and postprocessing was demonstrated for the fetal brain at 0.55T in a cohort of 38 fetal MRI scans. Robustness analysis was performed and placental measurements were taken for validation. High-quality T1 maps allowing the investigation of subregions in the brain were obtained and significant correlation with gestational age was demonstrated for fetal brain T1 maps ( Efficient, quantitative T1 mapping in the fetal brain was demonstrated on a clinical 0.55T MRI scanner, providing foundations for both future research and clinical applications including low-field specific T1-weighted acquisitions.

Identifiants

pubmed: 38968093
doi: 10.1002/mrm.30193
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Subventions

Organisme : Deutsche Forschungs Gemeinschaft (DFG) and Heisenberg
ID : 502024488
Organisme : Health Services and Delivery Research Programme
ID : NIHR3016640
Organisme : Wellcome/EPSRC Centre for Medical Engineering
ID : WT203148/Z/16/Z
Organisme : UK Research and Innovation
ID : MR/T018119/1

Informations de copyright

© 2024 The Author(s). Magnetic Resonance in Medicine published by Wiley Periodicals LLC on behalf of International Society for Magnetic Resonance in Medicine.

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Auteurs

Jordina Aviles Verdera (J)

Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK.
Biomedical Engineering Department, School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK.

Raphael Tomi-Tricot (R)

Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK.
Biomedical Engineering Department, School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK.
MR Research Collaborations, Siemens Healthcare Limited, Camberley, UK.

Lisa Story (L)

Women's Health, GSTT, London, UK.

Mary A Rutherford (MA)

Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK.
Biomedical Engineering Department, School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK.

Sebastien Ourselin (S)

Biomedical Engineering Department, School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK.

Joseph V Hajnal (JV)

Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK.
Biomedical Engineering Department, School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK.

Shaihan J Malik (SJ)

Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK.
Biomedical Engineering Department, School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK.

Jana Hutter (J)

Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK.
Biomedical Engineering Department, School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK.
Smart Imaging Lab, Radiological Institute, University Hospital Erlangen, Erlangen, Germany.

Classifications MeSH