Muscle MRI Outlining of Neuromuscular Diseases Using Artificial Intelligence

April 1, 2025 updated by: Bjørk Teitsdóttir, Rigshospitalet, Denmark

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.

Study Overview

Status

Not yet recruiting

Conditions

Intervention / Treatment

Study Type

Observational

Enrollment (Estimated)

120

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Contact

Study Contact Backup

  • Name: John Vissing, Professor

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

  • Adult
  • Older Adult

Accepts Healthy Volunteers

No

Sampling Method

Non-Probability Sample

Study Population

Patients will be recruited from Copenhagen Neuromuscular Centre.

Description

Inclusion Criteria:

  • Genetically verified diagnosis of neuromuscular diseases.
  • Age above 18 years

Exclusion Criteria:

  • 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

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

Cohorts and Interventions

Group / Cohort
Intervention / Treatment
Becker muscular dystrophy
MRI scans
Other: No intervention
No intervention.
HypoPP
MRI scans
Other: No intervention
No intervention.
FSHD
MRI scans
Other: No intervention
No intervention.

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Difference in fat fraction between manual and AI outlining.
Time Frame: Analysis of the muscle fat fraction takes 1 hour per patient.
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 Outcome Measures

Outcome Measure
Measure Description
Time Frame
Correlation between Manual/AI outlining discrepancies and disease severity
Time Frame: The analysis of the MRI takes around an hour
Investigate if the difference between manual outlining and AI outlining increases the more advanced stage the disease is. A correlation analysis will be made between manual/AI differences and fat fraction in lower back, thigh, and calf.
The analysis of the MRI takes around an hour

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Sponsor

Rigshospitalet, Denmark

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Estimated)

May 1, 2025

Primary Completion (Estimated)

January 1, 2035

Study Completion (Estimated)

January 1, 2035

Study Registration Dates

First Submitted

April 1, 2025

First Submitted That Met QC Criteria

April 1, 2025

First Posted (Estimated)

April 8, 2025

Study Record Updates

Last Update Posted (Estimated)

April 8, 2025

Last Update Submitted That Met QC Criteria

April 1, 2025

Last Verified

April 1, 2025

More Information

Terms related to this study

Keywords

Additional Relevant MeSH Terms

Other Study ID Numbers

  • 115991

Plan for Individual participant data (IPD)

Plan to Share Individual Participant Data (IPD)?

UNDECIDED

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

No

product manufactured in and exported from the U.S.

No

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

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