Adams School of Dentistry, University of North Carolina, Chapel Hill, NC, USA.
Department of Rehabilitation Medicine, University of Minnesota Medical School, Minneapolis, MN, USA.
Int J Oral Sci. 2023 Dec 28;15(1):58. doi: 10.1038/s41368-023-00254-z.
Chronic Painful Temporomandibular Disorders (TMD) are challenging to diagnose and manage due to their complexity and lack of understanding of brain mechanism. In the past few decades' neural mechanisms of pain regulation and perception have been clarified by neuroimaging research. Advances in the neuroimaging have bridged the gap between brain activity and the subjective experience of pain. Neuroimaging has also made strides toward separating the neural mechanisms underlying the chronic painful TMD. Recently, Artificial Intelligence (AI) is transforming various sectors by automating tasks that previously required humans' intelligence to complete. AI has started to contribute to the recognition, assessment, and understanding of painful TMD. The application of AI and neuroimaging in understanding the pathophysiology and diagnosis of chronic painful TMD are still in its early stages. The objective of the present review is to identify the contemporary neuroimaging approaches such as structural, functional, and molecular techniques that have been used to investigate the brain of chronic painful TMD individuals. Furthermore, this review guides practitioners on relevant aspects of AI and how AI and neuroimaging methods can revolutionize our understanding on the mechanisms of painful TMD and aid in both diagnosis and management to enhance patient outcomes.
慢性疼痛性颞下颌关节紊乱（TMD）由于其复杂性和对大脑机制的理解不足，诊断和治疗具有挑战性。在过去几十年中，神经影像学研究已经阐明了疼痛调节和感知的神经机制。神经影像学的进步弥合了大脑活动与疼痛主观体验之间的差距。神经影像学也朝着分离慢性疼痛性 TMD 的神经机制迈出了一步。最近，人工智能（AI）通过自动化以前需要人类智能完成的任务，正在改变各个领域。AI 已经开始有助于识别、评估和理解疼痛性 TMD。AI 和神经影像学在理解慢性疼痛性 TMD 的病理生理学和诊断中的应用仍处于早期阶段。本综述的目的是确定已经用于研究慢性疼痛性 TMD 个体大脑的当代神经影像学方法，如结构、功能和分子技术。此外，本综述指导从业者了解 AI 的相关方面，以及 AI 和神经影像学方法如何彻底改变我们对疼痛性 TMD 机制的理解，并有助于诊断和管理，以改善患者的预后。
