Recent advances and educational strategies in diagnostic imaging for temporomandibular disorders: a narrative literature review.

Abstract

Introduction: Temporomandibular disorders (TMD) are a group of orofacial conditions characterized by pain and dysfunction of the temporomandibular joint (TMJ) and surrounding musculature. Imaging plays a crucial role in diagnosis and treatment planning. However, educational content on TMD imaging in medical and dental curricula has lagged behind recent technological advances.

Methods: This review analyzes the current status of TMD imaging education based on a synthesis of literature and educational practices. It highlights discrepancies across institutional curricula and evaluates emerging strategies such as interdisciplinary learning, artificial intelligence (AI)-assisted tools, and simulation-based training.

Results: TMD imaging education is found to be inconsistent and underdeveloped globally, with significant variability in curriculum design and limited integration of modern imaging technologies. Current training programs lack standardized guidelines, resulting in knowledge gaps and increased risk of clinical misjudgment. Early findings suggest that AI and simulation tools can enhance educational outcomes.

Discussion: To bridge the gap between clinical practice and technology, a standardized, evidence-based educational framework is essential. Future strategies should include interprofessional collaboration, AI-driven diagnostic support, and immersive simulation environments. Implementing these measures will enable clinicians to accurately interpret TMD imaging and improve patient care.