Titre
Clinical Applications, Challenges, and Recommendations for Artificial Intelligence in Musculoskeletal and Soft-Tissue Ultrasound: AJR Expert Panel Narrative Review.
Type
article
Institution
UNIL/CHUV/Unisanté + institutions partenaires
Périodique
AJR. American journal of roentgenology
Auteur(s)
Yi, P.H.
Auteure/Auteur
Garner, H.W.
Auteure/Auteur
Hirschmann, A.
Auteure/Auteur
Jacobson, J.A.
Auteure/Auteur
Omoumi, P.
Auteure/Auteur
Oh, K.
Auteure/Auteur
Zech, J.R.
Auteure/Auteur
Lee, Y.H.
Auteure/Auteur
Liens vers les personnes
Liens vers les unités
ISSN
1546-3141
Statut éditorial
Publié
Date de publication
2024-03
Volume
222
Numéro
3
Première page
e2329530
Peer-reviewed
Oui
Langue
anglais
Notes
Publication types: Journal Article ; Review
Publication Status: ppublish
Publication Status: ppublish
Résumé
Artificial intelligence (AI) is increasingly used in clinical practice for musculoskeletal imaging tasks, such as disease diagnosis and image reconstruction. AI applications in musculoskeletal imaging have focused primarily on radiography, CT, and MRI. Although musculoskeletal ultrasound stands to benefit from AI in similar ways, such applications have been relatively underdeveloped. In comparison with other modalities, ultrasound has unique advantages and disadvantages that must be considered in AI algorithm development and clinical translation. Challenges in developing AI for musculoskeletal ultrasound involve both clinical aspects of image acquisition and practical limitations in image processing and annotation. Solutions from other radiology subspecialties (e.g., crowdsourced annotations coordinated by professional societies), along with use cases (most commonly rotator cuff tendon tears and palpable soft-tissue masses), can be applied to musculoskeletal ultrasound to help develop AI. To facilitate creation of high-quality imaging datasets for AI model development, technologists and radiologists should focus on increasing uniformity in musculoskeletal ultrasound performance and increasing annotations of images for specific anatomic regions. This Expert Panel Narrative Review summarizes available evidence regarding AI's potential utility in musculoskeletal ultrasound and challenges facing its development. Recommendations for future AI advancement and clinical translation in musculoskeletal ultrasound are discussed.
PID Serval
serval:BIB_C3097CD37173
PMID
Open Access
Oui
Date de création
2023-07-13T11:53:48.208Z
Date de création dans IRIS
2025-05-21T00:17:59Z