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• Review •
Advances in the application of artificial intelligence and mri in the diagnosis of triangular fibrocartilage complex injuries
GAO Yue  LI Yifan  SHI Shiji  WANG Shanshan 

DOI:10.12015/issn.1674-8034.2026.05.034.


[Abstract] At present, magnetic resonance imaging (MRI) is recognized as the main imaging modality for detecting triangular fibrocartilage complex (TFCC) injuries and can comprehensively assess the soft tissue conditions of the wrist joint. However, its complex and delicate structure makes it difficult for radiologists to diagnose. Arthroscopy is currently recognized as the gold standard for the diagnosis of TFCC injuries. Nevertheless, its invasive nature, limited visual field, and operator-dependent subjectivity may lead to iatrogenic trauma to patients. Artificial Intelligence (AI) has emerged as a prominent focus in medical imaging research, presenting novel opportunities for the precise and non-invasive evaluation of TFCC injuries. However, AI-based research on TFCC injuries remains in the nascent stage, with a paucity of systematic synthesis of application progress and challenges across domestic and international explorations. This review aims to summarize the current state of AI applications in TFCC injury diagnosis and the challenges encountered, delineate the limitations of existing research, and explore prospective research directions. By doing so, it seeks to provide innovative insights for future studies and offer a reference framework to inform clinical practice and enhance diagnostic and therapeutic efficacy.
[Keywords] triangular fibrocartilage complex；magnetic resonance imaging；machine learning；radiomics；deep learning；diagnosis

GAO Yue1, 2   LI Yifan2   SHI Shiji2   WANG Shanshan1, 2*  

1 Department of Radiology, Affiliated Hospital of Binzhou Medical College, Binzhou 256603, China

2 School of Medical Imaging, Shandong Medical And Pharmaceutical University, Yantai 264003, China

Corresponding author: WANG S S, E-mail: wss3256590@126.com

Conflicts of interest   None.

Received  2026-01-04
Accepted  2026-05-05
DOI: 10.12015/issn.1674-8034.2026.05.034
DOI:10.12015/issn.1674-8034.2026.05.034.

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