SNR analysis of contrast-enhanced MR imaging for early detection of rheumatoid arthritis.


Journal

PloS one
ISSN: 1932-6203
Titre abrégé: PLoS One
Pays: United States
ID NLM: 101285081

Informations de publication

Date de publication:
2019
Historique:
received: 29 11 2018
accepted: 14 02 2019
entrez: 2 3 2019
pubmed: 2 3 2019
medline: 30 11 2019
Statut: epublish

Résumé

To investigate whether signal to noise (SNR) analysis of contrast-enhanced MRI gives additional benefit for early disease detection by Magnetic Resonance Imaging (MRI) of experimental rheumatoid arthritis (RA) in a small animal model. We applied contrast-enhanced MRI at 7T in DBA mice with or without collagen-induced arthritis (CIA). Clinical score, OMERACT RAMRIS analysis and analysis of signal to noise ratios (SNR) of regions of interest in RA bearing mice, methotrexate/methylprednisolone acetate treated RA and control animals were compared with respect to benefit for early diagnosis. While treated RA and control animals did not show signs of RA activity in any of the above-mentioned scoring methods at any time point analyzed, RA animals revealed characteristic signs of RA in RAMRIS at the same time point when RA was detected clinically through scoring of the paws. The MR-based SNR analysis detected signs of synovitis, the earliest indication of RA, not only in late clinical stages, but also at an early stage when little or no clinical signs of RA were present in CIA animals and RAMRIS did not allow a distinct early detection. SNR analysis of contrast-enhanced MR imaging provides additional benefit for early arthritis detection in CIA mice.

Identifiants

pubmed: 30822342
doi: 10.1371/journal.pone.0213082
pii: PONE-D-18-34226
pmc: PMC6396898
doi:

Substances chimiques

Collagen 9007-34-5

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

e0213082

Déclaration de conflit d'intérêts

The authors have declared that no competing interests exist.

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Auteurs

Florian T Gassert (FT)

Department of Diagnostic and Interventional Radiology, Klinikum rechts der Isar, Technische Universitaet Muenchen, Munich, Germany.

Felix G Gassert (FG)

Department of Diagnostic and Interventional Radiology, Klinikum rechts der Isar, Technische Universitaet Muenchen, Munich, Germany.

Geoffrey J Topping (GJ)

Department of Nuclear Medicine, Klinikum rechts der Isar, Technische Universitaet Muenchen, Munich, Germany.

Ernst J Rummeny (EJ)

Department of Diagnostic and Interventional Radiology, Klinikum rechts der Isar, Technische Universitaet Muenchen, Munich, Germany.

Moritz Wildgruber (M)

Department of Diagnostic and Interventional Radiology, Klinikum rechts der Isar, Technische Universitaet Muenchen, Munich, Germany.
Translational Research Imaging Center, Department of Clinical Radiology, Universitätsklinikum Muenster, Muenster, Germany.

Reinhard Meier (R)

Department of Diagnostic and Interventional Radiology, Klinikum rechts der Isar, Technische Universitaet Muenchen, Munich, Germany.

Melanie A Kimm (MA)

Department of Diagnostic and Interventional Radiology, Klinikum rechts der Isar, Technische Universitaet Muenchen, Munich, Germany.

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Classifications MeSH