Temporomandibular disorders (TMDs), such as myofascial pain of the masticatory muscles and degenerative joint disease of the temporomandibular joint (TMJ), affect over 10 million Americans, have annual health care and societal costs estimated to be $750,000,000, and are recognized as a significant women's health problem. To date, it is unknown if there are gender based interactions between the variables of neuromuscular organization of the masticatory muscles and static mechanics that are significant in the pathogenesis of some TMDs. Our long-term goals are to improve the understanding of the role of mechanics in TMDs and explore the reason for its predilection in women. To achieve this goal, the proposed study will use validated computer-assisted numerical model predictions of muscle and TMJ forces in subjects with and without TMDs.
Specific Aim #1 will establish that the neuromuscular objective of minimization of joint loads is the basis of sagittal TMJ eminence shape in subjects with and without TMDs. Minimization of joint loads is a leading candidate objective since intracapsular stresses would be reduced, thereby reducing potential for fatigue failure of TMJ tissues.
Specific Aim #2 will demonstrate that the neuromuscular objectives for muscle force allocation during biting are not significantly different in individuals with and without TMDs. We hypothesize that the neuromuscular objectives of a) Minimization of joint loads, and/or b) Minimization of muscle effort, explain the apportionment of muscle forces during biting in humans.
Specific Aim #3 will demonstrate that for a given bite force, muscle and TMJ forces are larger in 1) subjects with TMDs compared to healthy subjects, and 2) women compared to men. We expect that numerical models, validated by comparing model predictions for a given subject with results measured from that subject, can be used to assess and compare variables that predispose higher muscle and TMJ forces. The impact of this project on health is the provision of clinical tools (validated numerical models) for TMDs that will: identify susceptible people, diagnose problematic structural relationships that could be corrected by surgery or other treatments, and provide essential information for future tissue engineering research.
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