Neuroimaging and artificial intelligence for assessment of chronic painful temporomandibular disorders-a comprehensive review.

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.

Ultrasonographic assessment of the swelling of the human masseter muscle after static and dynamic activity.

Work-related fatigue, pain and disorders in skeletal muscles have been related to prolonged static and dynamic activity. Such contractions have been shown to impair blood flow and increase muscle thickness and fluid. In the present study the effect of static and dynamic activity was evaluated from changes in masseter thickness as a measure of oedema, simultaneously with assessment of perceived pain/discomfort and cardiovascular responses. As static activity, fourteen young healthy women bit at 15% maximal voluntary contraction on bite-force transducers in the molar regions until exhaustion or 20 min at maximum (median endurance time 7.1 min). For dynamic activity, the same individuals chewed gum unilaterally until exhaustion or 40 min at maximum (all endured 40 min) with a cycle time of 725 ms, an average load of 9.3% of maximal electromyographic activity (maxEMG) and a peak mean voltage of 54.3% of maxEMG. Muscle thickness was measured by ultrasonography at the mid-portion of the ipsilateral masseter. Immediately after exercise, muscle thickness was significantly increased, more after static (14.0%) than dynamic (8.6%), and returned to pre-exercise values after 20-min recovery. Visual analogue scales (VAS) revealed the concomitant occurrence of pain (static 11.9 VAS%; dynamic 5.9 VAS%), and discomfort (static 8.1 VAS%; dynamic 5.9 VAS%), and both sensations decreased to pre-exercise values after 20-min recovery. Systolic blood pressure increased significantly, more during static (12.5%) than dynamic activity (4.3%), whereas heart rate rose significantly only during dynamic exercise (13.3%). Hence, activity was associated with muscular swelling and pain, and, despite the relatively small size of the masticatory muscles, also with general cardiovascular responses.