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.
Age range
18 Years
Sex
ALL
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AI-rewrites the medical criteria so a patient or caregiver can understand them. Always confirm with the trial site.
Bring these to your next appointment. They're a starting point for a shared conversation — not a sign you qualify or a recommendation to enrol.
Generated to help you prepare — always confirm anything about your own eligibility and care with the study team and your doctor.
The trial coordinator is the person who runs the study day to day. These cover the practical side — logistics, costs, and what taking part would actually mean for your life. The study team confirms whether you meet the criteria; these are questions to ask, not a sign you qualify.
A starting point for the conversation — always confirm anything about your own eligibility, costs, and care with the study team and your doctor.
Difference in fat fraction between manual and AI outlining.
Timeframe: Analysis of the muscle fat fraction takes 1 hour per patient.