Muscle MRI in patients with dysferlinopathy: Pattern recognition and implications for clinical trials

Jordi Diaz-Manera, Roberto Fernandez-Torron, Jaume Llauger, Meredith K. James, Anna Mayhew, Fiona E. Smith, Ursula R. Moore, Andrew M. Blamire, Pierre G. Carlier, Laura Rufibach, Plavi Mittal, Michelle Eagle, Marni Jacobs, Tim Hodgson, Dorothy Wallace, Louise Ward, Mark Smith, Roberto Stramare, Alessandro Rampado, Noriko SatoTakeshi Tamaru, Bruce Harwick, Susana Rico Gala, Suna Turk, Eva M. Coppenrath, Glenn Foster, David Bendahan, Yann Le Fur, Stanley T. Fricke, Hansel Otero, Sheryl L. Foster, Anthony Peduto, Anne Marie Sawyer, Heather Hilsden, Hanns Lochmuller, Ulrike Grieben, Simone Spuler, Carolina Tesi Rocha, John W. Day, Kristi J. Jones, Diana X. Bharucha-Goebel, Emmanuelle Salort-Campana, Matthew Harms, Alan Pestronk, Sabine Krause, Olivia Schreiber-Katz, Maggie C. Walter, Carmen Paradas, Jean Yves Hogrel, Tanya Stojkovic, Shin'ichi Takeda, Madoka Mori-Yoshimura, Elena Bravver, Susan Sparks, Luca Bello, Claudio Semplicini, Elena Pegoraro, Jerry R. Mendell, Kate Bushby, Volker Straub

Research output: Contribution to journalArticlepeer-review

87 Scopus citations

Abstract

Background and objective Dysferlinopathies are a group of muscle disorders caused by mutations in the DYSF gene. Previous muscle imaging studies describe a selective pattern of muscle involvement in smaller patient cohorts, but a large imaging study across the entire spectrum of the dysferlinopathies had not been performed and previous imaging findings were not correlated with functional tests. Methods We present cross-sectional T1-weighted muscle MRI data from 182 patients with genetically confirmed dysferlinopathies. We have analysed the pattern of muscles involved in the disease using hierarchical analysis and presented it as heatmaps. Results of the MRI scans have been correlated with relevant functional tests for each region of the body analysed. Results In 181 of the 182 patients scanned, we observed muscle pathology on T1-weighted images, with the gastrocnemius medialis and the soleus being the most commonly affected muscles. A similar pattern of involvement was identified in most patients regardless of their clinical presentation. Increased muscle pathology on MRI correlated positively with disease duration and functional impairment. Conclusions The information generated by this study is of high diagnostic value and important for clinical trial development. We have been able to describe a pattern that can be considered as characteristic of dysferlinopathy. We have defined the natural history of the disease from a radiological point of view. These results enabled the identification of the most relevant regions of interest for quantitative MRI in longitudinal studies, such as clinical trials. Clinical trial registration NCT01676077.

Original languageEnglish
Pages (from-to)1071-1081
Number of pages11
JournalJournal of Neurology, Neurosurgery and Psychiatry
Volume89
Issue number10
DOIs
StatePublished - Oct 1 2018

Keywords

  • dysferlinopathy
  • muscle MRI
  • muscular dystrophy
  • outcome measures

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