Related Experiment Video
Updated: Feb 11, 2026

Characterizing Exon Skipping Efficiency in DMD Patient Samples in Clinical Trials of Antisense Oligonucleotides
Published on: May 7, 2020
Muscle MRI in patients with dysferlinopathy: pattern recognition and implications for clinical trials
Jordi Diaz-Manera1,2, Roberto Fernandez-Torron3,4, Jaume LLauger5
1Centro de Investigación Biomédica en Red en Enfermedades Raras (CIBERER), Barcelona, Spain.
Muscle MRI reveals a characteristic pattern in dysferlinopathies, with gastrocnemius medialis and soleus muscles most affected. This imaging approach aids diagnosis and clinical trial development for this genetic muscle disorder.
Area of Science:
- Neurology
- Radiology
- Genetics
Background:
- Dysferlinopathies are genetic muscle disorders caused by mutations in the DYSF gene.
- Previous muscle imaging studies were limited in scope and lacked correlation with functional tests.
Purpose of the Study:
- To perform a large-scale muscle MRI study across the spectrum of dysferlinopathies.
- To correlate imaging findings with functional tests.
- To establish a characteristic imaging pattern for diagnostic and clinical trial purposes.
Main Methods:
- Cross-sectional T1-weighted muscle MRI data from 182 genetically confirmed dysferlinopathy patients.
- Hierarchical analysis and heatmaps to analyze muscle involvement patterns.
- Correlation of MRI findings with relevant functional tests.
Main Results:
- Muscle pathology observed in 181/182 patients.
- Gastrocnemius medialis and soleus muscles were most frequently affected.
- Increased MRI pathology correlated with longer disease duration and greater functional impairment.
Conclusions:
- A characteristic muscle MRI pattern for dysferlinopathies was identified.
- Imaging findings provide diagnostic value and insights into disease natural history.
- Identified key regions of interest for quantitative MRI in future clinical trials.
Related Concept Videos
Clinical Trials
There are four phases in a clinical trial. A phase one...
Clinical Trials: Overview
Statistical Software for Data Analysis and Clinical Trials
Trial and Error and Algorithm
Fixed Action Patterns
Patterns of Fever

