Harnessing Artificial Intelligence for Shoulder Ultrasonography: A Narrative Review.

Journal: Journal of imaging informatics in medicine
Published Date: Sep 12, 2025

Abstract

Shoulder pain is a common musculoskeletal complaint requiring accurate imaging for diagnosis and management. Ultrasound is favored for its accessibility, dynamic imaging, and high-resolution soft tissue visualization. However, its operator dependency and variability in interpretation present challenges. Recent advancements in artificial intelligence (AI), particularly deep learning algorithms like convolutional neural networks, offer promising applications in musculoskeletal imaging, enhancing diagnostic accuracy and efficiency. This narrative review explores AI integration in shoulder ultrasound, emphasizing automated pathology detection, image segmentation, and outcome prediction. Deep learning models have demonstrated high accuracy in grading bicipital peritendinous effusion and discriminating rotator cuff tendon tears, while machine learning techniques have shown efficacy in predicting the success of ultrasound-guided percutaneous irrigation for rotator cuff calcification. AI-powered segmentation models have improved anatomical delineation; however, despite these advancements, challenges remain, including the need for large, well-annotated datasets, model generalizability across diverse populations, and clinical validation. Future research should optimize AI algorithms for real-time applications, integrate multimodal imaging, and enhance clinician-AI collaboration.

Authors

  • Wei-Ting Wu
    Department of Physical Medicine and Rehabilitation and Community and Geriatric Research Center, National Taiwan University Hospital, Bei-Hu Branch, Taipei, Taiwan; Department of Physical Medicine and Rehabilitation, National Taiwan University College of Medicine, Taipei, Taiwan.
  • Yi-Chung Shu
    Institute of Applied Mechanics, College of Engineering, National Taiwan University, Taipei, Taiwan.
  • Che-Yu Lin
    Institute of Applied Mechanics, College of Engineering, National Taiwan University, Taipei, Taiwan.
  • Consuelo B Gonzalez-Suarez
    Research Center for Health Science, University of Santo Tomas, Manila, Philippines.
  • Levent Özçakar
    Department of Physical and Rehabilitation Medicine, Hacettepe University Medical School, Ankara, Turkey.
  • Ke-Vin Chang
    Department of Physical Medicine and Rehabilitation and Community and Geriatric Research Center, National Taiwan University Hospital, Bei-Hu Branch, Taipei, Taiwan; Department of Physical Medicine and Rehabilitation, National Taiwan University College of Medicine, Taipei, Taiwan; Center for Regional Anesthesia and Pain Medicine, Wang-Fang Hospital, Taipei Medical University, Taipei, Taiwan. Electronic address: [email protected].

Keywords

No keywords available for this article.

External Resources

Popular Topics
Recent Journals