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Myo-Guide: A Machine Learning-Based Web Application for Neuromuscular Disease Diagnosis With Mri Publisher Pubmed



Verdudiaz J1 ; Bolanodiaz C1 ; Gonzalezchamorro A1 ; Fitzsimmons S1 ; Warmanchardon J2, 3 ; Kocak G1 ; Mucidaalvim D1 ; Smith I4 ; Vissing J5 ; Poulsen N5 ; Luo S6 ; Dominguezgonzalez C7 ; Bermejoguerrero L7 ; Gomezandres D8 Show All Authors
Authors
  1. Verdudiaz J1
  2. Bolanodiaz C1
  3. Gonzalezchamorro A1
  4. Fitzsimmons S1
  5. Warmanchardon J2, 3
  6. Kocak G1
  7. Mucidaalvim D1
  8. Smith I4
  9. Vissing J5
  10. Poulsen N5
  11. Luo S6
  12. Dominguezgonzalez C7
  13. Bermejoguerrero L7
  14. Gomezandres D8
  15. Sotoca J9
  16. Pichiecchio A10, 11
  17. Nicolosi S12
  18. Monforte M14
  19. Brogna C15
  20. Mercuri E16
  21. Bevilacqua J17
  22. Diazjara J17
  23. Pizarrogalleguillos B18
  24. Krkoska P19
  25. Alonsoperez J20
  26. Olive M21, 22, 23
  27. Niks E24
  28. Kan H25
  29. Lilleker J26
  30. Roberts M26
  31. Buchignani B27
  32. Shin J28
  33. Esselin F29
  34. Lebars E30
  35. Childs A31
  36. Malfatti E32
  37. Sarkozy A33
  38. Perry L33
  39. Sudhakar S34
  40. Zanoteli E35
  41. Dipace F35
  42. Matthews E36
  43. Attarian S37
  44. Bendahan D38
  45. Garibaldi M39
  46. Fionda L40
  47. Alonsojimenez A41
  48. Carlier R42
  49. Okhovat A43
  50. Nafissi S43
  51. Nalini A44
  52. Vengalil S44
  53. Hollingsworth K45
  54. Marinibettolo C1
  55. Straub V1
  56. Tasca G1
  57. Bacardit J46
  58. Diazmanera J1

Source: Journal of Cachexia, Sarcopenia and Muscle Published:2025


Abstract

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. © 2025 The Author(s). Journal of Cachexia, Sarcopenia and Muscle published by Wiley Periodicals LLC.