Muscle MRI Outlining of Neuromuscular Diseases Using Artificial Intelligence
NCT ID: NCT06917430
Last Updated: 2025-04-08
Study Results
The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.
Basic Information
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NOT_YET_RECRUITING
120 participants
OBSERVATIONAL
2025-05-01
2035-01-01
Brief Summary
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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.
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Detailed Description
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Conditions
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Study Design
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OTHER
CROSS_SECTIONAL
Study Groups
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Becker muscular dystrophy
MRI scans
No intervention
No intervention.
HypoPP
MRI scans
No intervention
No intervention.
FSHD
MRI scans
No intervention
No intervention.
Interventions
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No intervention
No intervention.
Eligibility Criteria
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Inclusion Criteria
* Age above 18 years
Exclusion Criteria
* Competing disorders and other muscle disorders, which may alter measurements. The investigator will decide whether the competing disorder can significantly influence the results
18 Years
ALL
No
Sponsors
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Rigshospitalet, Denmark
OTHER
Responsible Party
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Bjørk Teitsdóttir
Stud.med
Central Contacts
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John Vissing, Professor
Role: CONTACT
Other Identifiers
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115991
Identifier Type: -
Identifier Source: org_study_id
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