MedTrace Logo

Muscle MRI Outlining of Neuromuscular Diseases Using Artificial Intelligence

NCT06917430 · Status: NOT_YET_RECRUITING · Type: OBSERVATIONAL · Enrollment: 120

Last updated 2025-04-08

No results posted yet for this study

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.

Conditions

  • Becker Muscular Dystrophy
  • FSHD - Facioscapulohumeral Muscular Dystrophy
  • Hypokalemic Periodic Paralysis

Interventions

OTHER

No intervention

No intervention.

Sponsors & Collaborators

  • Rigshospitalet, Denmark

    lead OTHER

Eligibility

Min Age
18 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2025-05-01
Primary Completion
2035-01-01
Completion
2035-01-01

More Related Trials

Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT06917430 on ClinicalTrials.gov