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Myo-Guide: A Machine Learning-Based Web Application for Neuromuscular Disease Diagnosis With MRI

J. Verdu-Diaz, C. Bolano-Díaz, A. Gonzalez-Chamorro, S. Fitzsimmons, J. Warman-Chardon, GS. Kocak, D. Mucida-Alvim, IC. Smith, J. Vissing, NS. Poulsen, S. Luo, C. Domínguez-González, L. Bermejo-Guerrero, D. Gomez-Andres, J. Sotoca, A....

. 2025 ; 16 (3) : e13815. [pub] -

Jazyk angličtina Země Německo

Typ dokumentu časopisecké články

Perzistentní odkaz   https://www.medvik.cz/link/bmc25015467

Grantová podpora
22GRO-PG24-0575 Muscular Dystrophy UK
24GRO-PG24-0736-1 Muscular Dystrophy UK
23444 AFM-Telethon
NIHR203309 Newcastle Biomedical Research Centre
National Institute for Health and Care Research

BACKGROUND: Neuromuscular diseases (NMDs) are rare disorders characterized by progressive muscle fibre loss, leading to replacement by fibrotic and fatty tissue, muscle weakness and disability. Early diagnosis is critical for therapeutic decisions, care planning and genetic counselling. Muscle magnetic resonance imaging (MRI) has emerged as a valuable diagnostic tool by identifying characteristic patterns of muscle involvement. However, the increasing complexity of these patterns complicates their interpretation, limiting their clinical utility. Additionally, multi-study data aggregation introduces heterogeneity challenges. This study presents a novel multi-study harmonization pipeline for muscle MRI and an AI-driven diagnostic tool to assist clinicians in identifying disease-specific muscle involvement patterns. METHODS: We developed a preprocessing pipeline to standardize MRI fat content across datasets, minimizing source bias. An ensemble of XGBoost models was trained to classify patients based on intramuscular fat replacement, age at MRI and sex. The SHapley Additive exPlanations (SHAP) framework was adapted to analyse model predictions and identify disease-specific muscle involvement patterns. To address class imbalance, training and evaluation were conducted using class-balanced metrics. The model's performance was compared against four expert clinicians using 14 previously unseen MRI scans. RESULTS: Using our harmonization approach, we curated a dataset of 2961 MRI samples from genetically confirmed cases of 20 paediatric and adult NMDs. The model achieved a balanced accuracy of 64.8% ± 3.4%, with a weighted top-3 accuracy of 84.7% ± 1.8% and top-5 accuracy of 90.2% ± 2.4%. It also identified key features relevant for differential diagnosis, aiding clinical decision-making. Compared to four expert clinicians, the model obtained the highest top-3 accuracy (75.0% ± 4.8%). The diagnostic tool has been implemented as a free web platform, providing global access to the medical community. CONCLUSIONS: The application of AI in muscle MRI for NMD diagnosis remains underexplored due to data scarcity. This study introduces a framework for dataset harmonization, enabling advanced computational techniques. Our findings demonstrate the potential of AI-based approaches to enhance differential diagnosis by identifying disease-specific muscle involvement patterns. The developed tool surpasses expert performance in diagnostic ranking and is accessible to clinicians worldwide via the Myo-Guide online platform.

Advanced Imaging and AI Center Mondino IRCCS Foundation Pavia Italy

Aix Marseille University CRMBM CNRS UMR 7339 Marseille France

Biomedical Research Institute Sant Pau Barcelona Spain

C J Gorter MRI Center Department of Radiology Leiden University Medical Center Leiden The Netherlands

Centre de Référence des Maladies du Motoneurone Department of Neurology Montpellier University Hospital Montpellier France

Centro de Investigaciones Biomédicas en Red en Enfermedades Raras Madrid Spain

Copenhagen Neuromuscular Centre Rigshospitalet Copenhagen University Hospital Copenhagen Denmark

Department of Brain and Behavioural Sciences University of Pavia Pavia Italy

Department of Genetics Children's Hospital of Eastern Ontario Ottawa Canada

Department of Medicine The Ottawa Hospital Ottawa Canada

Department of Neurology Faculdade de Medicina da Universidade de São Paulo São Paulo Brazil

Department of Neurology Huashan Hospital Fudan University Shanghai China

Department of Neurology Leiden University Medical Center Leiden The Netherlands

Department of Neurology Pusan National University School of Medicine Busan Republic of Korea

Department of Neuroradiology Great Ormond Street Hospital for Children NHS Foundation Trust London UK

Department of Neuroradiology I2FH Platform Montpellier University Hospital Montpellier France

Department of Neuroscience Mental Health and Sensory Organs SAPIENZA University of Rome Rome Italy

Department of Translational Research and of New Surgical and Medical Technologies University of Pisa Pisa Italy

Dubowitz Neuromuscular Centre UCL Great Ormond Street Institute of Child Health and Great Ormond Street Hospital London UK

Fondazione Policlinico Universitario Agostino Gemelli Rome Italy

Hospital Clínico Universidad de Chile Santiago de Chile Chile

Hospital Universitari Vall d'Hebron Barcelona Spain

Interdisciplinary Computing and Complex BioSystems Research Group School of Computing Newcastle University Newcastle upon Tyne UK

John Walton Muscular Dystrophy Research Centre Newcastle University Newcastle upon Tyne UK

Leeds Teaching Hospitals NHS Trust Leeds UK

Mondino IRCCS Foundation Pavia Italy

National Institute of Mental Health and Neurosciences Bengaluru India

Neurology Department Shariati Hospital Neuromuscular Research Center Tehran University of Medical Sciences Tehran Iran

Neuromuscular and Rare Disease Centre Neurology Unit Sant'Andrea Hospital Rome Italy

Neuromuscular Disease Unit Neurology Department Hospital Universitario Nuestra Señora de Candelaria Tenerife Spain

Neuromuscular Disorders Unit Department of Neurology Hospital de la Santa Creu i Sant Pau Barcelona Spain

Neuromuscular Disorders Unit Neurology Department Hospital 12 de Octubre Madrid Spain

Neuromuscular Disorders Unit Neurology Department Hospital Universitari Vall d'Hebron Barcelona Spain

Neuromuscular Reference Center Department of Neurology Universitair Ziekenhuis van Antwerpen Universiteit Antwerpen Antwerp Belgium

Northern Care Alliance NHS Foundation Trust Manchester UK

Ottawa Hospital Research Institute Ottawa Canada

Paris Est University APHP Henri Mondor University Hospital Créteil France

Pediatric Neurology Department of Woman and Child Health and Public Health Child Health Area Università Cattolica del Sacro Cuore Rome Italy

Programa de Doctorado en Ciencias Médicas y Especialidad Escuela de Postgrado Facultad de Medicina Universidad de Chile Santiago Chile

Reference Center for Neuromuscular Disorders CHU La Timone Aix Marseille University Marseille France

St George's University and St George's University Hospitals NHS Foundation Trust London UK

Translational and Clinical Research Institute Newcastle University Newcastle upon Tyne UK

University Hospital Brno Brno Czech Republic

University Hospital Raymond Poincaré Garches France

University of Pavia

UOC di Neurologia Fondazione Policlinico Universitario Agostino Gemelli IRCCS Rome Italy

Citace poskytuje Crossref.org

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