Applications of artificial intelligence in imaging of musculoskeletal disorders: a systematic review of reviews

Background and Aims: The utilization of standard imaging techniques has grown significantly as a key component in managing patients with musculoskeletal disorders (MSD). Imaging impacts the efficiency, accuracy, and quality of radiology reports. Artificial intelligence (AI) offers the potential to streamline imaging procedures and better serve patient needs. Consequently, this systematic review of reviews was conducted in ۲۰۲۴ to examine the role of AI in MSD patient imaging. Methods: A systematic review of reviews examining AI applications in MSD imaging was performed according to PRISMA guidelines. Five databases—PubMed, Scopus, Embase, Web of Science, and ProQuest—were systematically searched for relevant studies from inception until March ۱۰, ۲۰۲۵. Backward and forward reference-checking techniques were additionally utilized to identify supplementary sources. Inclusion criteria were applied to titles, abstracts, and full texts. The study protocol was registered with the OSF database. Results: The most common applications of AI in the field of MSD imaging are ordering appropriate imaging tests to predict patients at risk of fracture, image interpretation consist of the determination of bone age, body composition measurements, screening for osteoporosis, evaluation of segmental spine pathology, fracture detection and classification, identifying and grading abnormal findings of osteoarthritis, diagnosis and outcome prediction of bone and soft-tissue tumors, awareness about appropriate positioning of orthopedic implants and their complications, automated examination protocoling, optimized scheduling, shorter MRI acquisition times, artifact-reduced and lower-dose CT scans, new methods for producing and using radiology reports, and workflow automation. Conclusion: AI applications in imaging include both interpretative and non-interpretative tasks. Overall, AI has the potential to enhance various areas of physiotherapy through the