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.

慢性疼痛性颞下颌疾病 (TMD) 由于其复杂性和缺乏对大脑机制的了解而难以诊断和治疗。在过去的几十年里，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和疼痛主观体验之间的差距。神经影像学在分离慢性疼痛 TMD 背后的神经机制方面也取得了长足的进步。最近，人工智能（AI）正在通过自动化以前需要人类智能才能完成的任务来改变各个领域。人工智能已经开始为痛苦的 TMD 的识别、评估和理解做出贡献。人工智能和神经影像学在理解慢性疼痛性 TMD 的病理生理学和诊断方面的应用仍处于早期阶段。本综述的目的是确定当代神经影像学方法，例如结构、功能和分子技术，这些方法已用于研究慢性疼痛 TMD 个体的大脑。此外，这篇综述指导从业者了解人工智能的相关方面，以及人工智能和神经影像方法如何彻底改变我们对痛苦 TMD 机制的理解，并帮助诊断和管理，以提高患者的治疗效果。