Thessaly Graft Index: An Artificial Intelligence-Based Index for the Assessment of Graft Integrity in ACL-Reconstructed Knees.

Journal: The Journal of bone and joint surgery. American volume
PMID: 39919170

Abstract

BACKGROUND: Magnetic resonance imaging (MRI) has proven to be a valuable noninvasive tool to evaluate graft integrity after anterior cruciate ligament (ACL) reconstruction. However, MRI protocols and interpretation methodologies are quite diverse, preventing comparisons of signal intensity across subsequent scans and independent investigations. The purpose of this study was to create an artificial intelligence (AI)-based index (Thessaly Graft Index [TGI]) for the evaluation of graft integrity following ACL reconstruction.

Authors

  • Georgios Chalatsis
    Department of Orthopaedic Surgery & Musculoskeletal Trauma, University Hospital of Larissa, School of Health Sciences, University of Thessaly, Larissa, Greece.
  • Athanasios Siouras
    AiDEAS, Tallinn, Estonia.
  • Vasileios Mitrousias
    Department of Orthopaedic Surgery & Musculoskeletal Trauma, University Hospital of Larissa, School of Health Sciences, University of Thessaly, Larissa, Greece.
  • Ilias Chantes
    Erasmus School of Economics, Erasmus School of Health Policy & Management, Erasmus University Rotterdam, Rotterdam, The Netherlands.
  • Serafeim Moustakidis
    AIDEAS OÜ, Narva mnt 5, Tallinn, Harju maakond, 10117, Estonia.
  • Dimitris Tsaopoulos
    Institute for Bio-Economy and Agri-Technology, Center of Research and Technology - Hellas, Marousi, Greece.
  • Marianna Vlychou
    Radiology Department, Medical School, University of Thessaly, Larisa, Greece.
  • Sotiris Tasoulis
    Department of Computer Science and Biomedical Informatics, School of Science, University of Thessaly, Lamia 35131, Greece.
  • Michael Hantes
    Department of Orthopedic Surgery, Faculty of Medicine, University of Thessaly, Larissa 41500, Greece.

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