Muscle MRI Outlining of Neuromuscular Diseases Using Artificial Intelligence
1 other identifier
observational
120
0 countries
N/A
Brief Summary
Background and aim: Neuromuscular diseases encompass a range of conditions affecting muscle cells, nerves, or the interaction between the two. A common pathological feature of these conditions is the pro-gressive replacement of muscle tissue with fat, which can be visualised using magnetic reso-nance imaging (MRI). MRI-based fat quantification serves as a key biomarker for disease characterisation, progression tracking, and treatment assessment. Currently, manual segmenta-tion of MRI scans for fat quantification is very time-consuming, requiring individual muscle delineation. Therefore, an artificial intelligence (AI) model is being developed to automate the segmentation. The aim of this study is to validate this AI model and assess its possibilities and limitations. Method: The study is ongoing. Retrospective MRI scans of patients with four different muscle diseases (anoctaminopathy, Becker muscular dystrophy, facioscapulohumeral muscular dystrophy, and hypokalemic periodic paralysis) are collected and manual delineation used for training the AI-model is being performed. The intramuscular fat fraction of individual muscles of the pelvis, thigh, and calf will be analysed using the AI model. The performance of the AI model will be compared to manual segmentation. The AI will be evaluated on metrics such as segmentation accuracy and time efficiency.
Trial Health
Trial Health Score
Automated assessment based on enrollment pace, timeline, and geographic reach
participants targeted
Target at P50-P75 for all trials
Started May 2025
Longer than P75 for all trials
Health score is calculated from publicly available data and should be used for screening purposes only.
Trial Relationships
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Study Timeline
Key milestones and dates
First Submitted
Initial submission to the registry
April 1, 2025
CompletedFirst Posted
Study publicly available on registry
April 8, 2025
CompletedStudy Start
First participant enrolled
May 1, 2025
CompletedPrimary Completion
Last participant's last visit for primary outcome
January 1, 2035
ExpectedStudy Completion
Last participant's last visit for all outcomes
January 1, 2035
April 8, 2025
April 1, 2025
9.7 years
April 1, 2025
April 1, 2025
Conditions
Keywords
Outcome Measures
Primary Outcomes (1)
Difference in fat fraction between manual and AI outlining.
The mean difference in MRI assessed intramuscular fat fraction in the lower back, thigh, and calf muscles between manual outlining and the outlining by the AI model.
Analysis of the muscle fat fraction takes 1 hour per patient.
Secondary Outcomes (1)
Correlation between Manual/AI outlining discrepancies and disease severity
The analysis of the MRI takes around an hour
Study Arms (3)
Becker muscular dystrophy
MRI scans
HypoPP
MRI scans
FSHD
MRI scans
Interventions
Eligibility Criteria
Patients will be recruited from Copenhagen Neuromuscular Centre.
You may qualify if:
- Genetically verified diagnosis of neuromuscular diseases.
- Age above 18 years
You may not qualify if:
- Contraindications to perform an MRI
- Competing disorders and other muscle disorders, which may alter measurements. The investigator will decide whether the competing disorder can significantly influence the results
Contact the study team to confirm eligibility.
Sponsors & Collaborators
MeSH Terms
Conditions
Condition Hierarchy (Ancestors)
Central Study Contacts
John Vissing, Professor
CONTACT
Study Design
- Study Type
- observational
- Observational Model
- OTHER
- Time Perspective
- CROSS SECTIONAL
- Sponsor Type
- OTHER
- Responsible Party
- PRINCIPAL INVESTIGATOR
- PI Title
- Stud.med
Study Record Dates
First Submitted
April 1, 2025
First Posted
April 8, 2025
Study Start
May 1, 2025
Primary Completion (Estimated)
January 1, 2035
Study Completion (Estimated)
January 1, 2035
Last Updated
April 8, 2025
Record last verified: 2025-04