REVIEW article
Front. Neurol.
Sec. Headache and Neurogenic Pain
Volume 16 - 2025 | doi: 10.3389/fneur.2025.1597312
This article is part of the Research TopicThe association between the nervous system and the stomatognathic system: from etiology to diagnosis and treatment of orofacial painView all 8 articles
Recent Advances and Educational Strategies in Diagnostic Imaging for Temporomandibular Disorders: A Narrative Literature Review
Provisionally accepted
- 1Department of Radiology, West China Hospital, Sichuan University, Chengdu, Sichuan Province, China
- 2State Key Laboratory of Oral Diseases, West China School of Stomatology, Sichuan University, Chengdu, Sichuan Province, China
- 3Department of Rehabilitation Medicine, West China Hospital, Sichuan University, Chengdu, Sichuan Province, China
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Temporomandibular disorders (TMD) encompass a complex group of orofacial conditions that cause dysfunction and pain in the jaw and surrounding areas. Imaging plays a critical adjunctive role in TMD assessment, providing detailed visualization of joint and muscle structures. Recent advances in these imaging techniques have improved diagnostic accuracy and clinical decision-making for TMD. However, the education of dental and medical curriculum in TMD imaging has not kept pace with technological advancements. This review describes the current status and problems of TMD imaging education and introduces interdisciplinary learning strategies, the role of artificial intelligence and simulation-based training, and future directions. Currently, TMD imaging education varies greatly among institutions, with inconsistent curriculum structures and a lack of standardized guidelines. The integration of advanced imaging technologies into training programs remains insufficient, resulting in gaps in clinician capabilities and the risk of misdiagnosis. Emerging technologies such as artificial intelligence-assisted image analysis show promise in improving learning outcomes. Standardized curricula, interprofessional collaboration, and evidence-based training methods are needed in the future to bridge the gap between technological advances and clinical practice. This includes combining artificial intelligence-driven diagnostic tools, simulation-based learning, and developing consensus-driven guidelines to ensure comprehensive TMD imaging education.Strengthening the educational framework will enable clinicians to accurately interpret imaging results and integrate them into overall patient management.
Keywords: Temporomandibular disorders, Diagnostic Imaging, curriculum development, Medical Education, artificial intelligence
Received: 21 Mar 2025; Accepted: 06 May 2025.
Copyright: © 2025 Zhao, Xiong, Li, Zhang, Yang and Ye. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Zheng Ye, Department of Radiology, West China Hospital, Sichuan University, Chengdu, 610041, Sichuan Province, China
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