7 Tesla MRI Liver Fat Quantification in Mice: Data Quality Assessment.
Data quality
Liver fat quantification
MRI
NAFLD.
PDFF
Small animal
Journal
Current medical imaging
ISSN: 1573-4056
Titre abrégé: Curr Med Imaging
Pays: United Arab Emirates
ID NLM: 101762461
Informations de publication
Date de publication:
2024
2024
Historique:
received:
19
06
2023
revised:
06
10
2023
accepted:
16
10
2023
medline:
23
2
2024
pubmed:
23
2
2024
entrez:
23
2
2024
Statut:
ppublish
Résumé
The objective of this study was to evaluate the robustness of proton density fat fraction (PDFF) data determined by magnetic resonance imaging (MRI) and spectroscopy (MRS) via spatially resolved error estimation. Using standard T2* relaxation time measurement protocols, The determined error maps helped excluding measurement errors as cause of unexpected local PDFF variations in the explanted liver. For in vivo measurements, severe error maps gave rise to doubts in the acquired PDFF maps and triggered an in-depth analysis of possible causes, yielding abdominal movement or bladder filling as in vivo occurring reasons for the increased errors. The combination of pixel-wise acquisition of PDFF data and the corresponding error maps allows for a more specific, spatially resolved evaluation of the PDFF value reliability.
Identifiants
pubmed: 38389373
pii: CMIR-EPUB-138463
doi: 10.2174/0115734056263741231117112245
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
1-10Subventions
Organisme : Deutsche Forschungsgemeinschaft (DFG, Bonn-Bad Godesberg, Germany)
ID : AB 453/2-1
Informations de copyright
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