255th ENMC workshop: Muscle imaging in idiopathic inflammatory myopathies. 15th January, 16th January and 22nd January 2021 - virtual meeting and hybrid meeting on 9th and 19th September 2022 in Hoofddorp, The Netherlands.


Journal

Neuromuscular disorders : NMD
ISSN: 1873-2364
Titre abrégé: Neuromuscul Disord
Pays: England
ID NLM: 9111470

Informations de publication

Date de publication:
Oct 2023
Historique:
received: 09 08 2023
revised: 20 08 2023
accepted: 25 08 2023
medline: 6 11 2023
pubmed: 29 9 2023
entrez: 28 9 2023
Statut: ppublish

Résumé

The 255th ENMC workshop on Muscle Imaging in Idiopathic Inflammatory myopathies (IIM) aimed at defining recommendations concerning the applicability of muscle imaging in IIM. The workshop comprised of clinicians, researchers and people living with myositis. We aimed to achieve consensus on the following topics: a standardized protocol for the evaluation of muscle images in various types of IIMs; the exact parameters, anatomical localizations and magnetic resonance imaging (MRI) techniques; ultrasound as assessment tool in IIM; assessment methods; the pattern of muscle involvement in IIM subtypes; the application of MRI as biomarker in follow-up studies and clinical trials, and the place of MRI in the evaluation of swallowing difficulty and cardiac manifestations. The following recommendations were formulated: In patients with suspected IIM, muscle imaging is highly recommended to be part of the initial diagnostic workup and baseline assessment. MRI is the preferred imaging modality due to its sensitivity to both oedema and fat accumulation. Ultrasound may be used for suspected IBM. Repeat imaging should be considered if patients do not respond to treatment, if there is ongoing diagnostic uncertainty or there is clinical or laboratory evidence of disease relapse. Quantitative MRI is established as a sensitive biomarker in IBM and could be included as a primary or secondary outcome measure in early phase clinical trials, or as a secondary outcome measure in late phase clinical trials. Finally, a research agenda was drawn up.

Identifiants

pubmed: 37770338
pii: S0960-8966(23)00709-5
doi: 10.1016/j.nmd.2023.08.014
pii:
doi:

Substances chimiques

Biomarkers 0

Types de publication

Clinical Conference

Langues

eng

Sous-ensembles de citation

IM

Pagination

800-816

Investigateurs

Jemima Albayda (J)
Yves Allenbach (Y)
Olivier Benveniste (O)
Pierre Carlier (P)
Louise Diederichsen (L)
Georges Demonceau (G)
Ingrid de Groot (I)
Anneke van der Kooi (A)
Kateřina Kubínová (K)
Pedro Machado (P)
Andrew Mammen (A)
Harmen Reyngoudt (H)
Roland Mischke (R)
Jasper Morrow (J)
Nicoló Pipitone (N)
Corinna Preusse (C)
Michael Rataj (M)
Lisa Rider (L)
Jens Schmidt (J)
Werner Stenzel (W)
Giorgio Tasca (G)
Jiří Vencovský (J)
Marianne de Visser (M)
Camiel Verhamme (C)

Informations de copyright

Copyright © 2023.

Déclaration de conflit d'intérêts

Declaration of Competing Interest JV and KK received support from the Czech Ministry of Health, Conceptual Development of Research Organization 00023728 (Institute of Rheumatology). LGR received support from the intramural research program of the National Instittute of Environmental Health Sciences, National Institutes of Health. All other participants declared no conflict of interest related to the workshop topic.

Auteurs

Marianne de Visser (M)

Department of Neurology, Amsterdam Neuroscience, Amsterdam University Medical Centre, Location Academic Medical Centre, University of Amsterdam, Amsterdam, The Netherlands. Electronic address: m.devisser@amsterdamumc.nl.

Pierre Carlier (P)

CEA, Orsay, Paris, France.

Jiří Vencovský (J)

Institute of Rheumatology, Department of Rheumatology, Charles University, Prague, Czech Republic.

Kateřina Kubínová (K)

Institute of Rheumatology, Department of Rheumatology, Charles University, Prague, Czech Republic.

Corinna Preusse (C)

Charité-Universitätsmedizin Berlin, Corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin Institute of Health Department of Neuropathology, Berlin, Germany.

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Classifications MeSH