Diagnostic and Therapeutic Approaches to Temporomandibular Dysfunction: History
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Subjects: Medicine, General & Internal
Contributor:
Brendan Moxley
,
William Stevens
,
Joel Sneed
,
Craig Pearl

Temporomandibular dysfunction (TMD) is a burgeoning area of study within the dental field. TMD is caused by abnormalities in the temporomandibular joint or muscles of mastication and can lead to pain, loss of function, and other complications.

  • novel diagnosis
  • temporomandibular dysfunction
  • therapeutic

1. Introduction

Temporomandibular dysfunction (TMD) is the second most common musculoskeletal disorder that causes pain and disability, affecting nearly 5% of Americans (~16 million people) [1][2][3][4]. TMD is a condition that can be symptom-free, but more often causes patients pain, discomfort, and dysfunction that can be profoundly debilitating. The treatment costs and quality of life burden can be significant on these patients [5].
In fact, the proportion of TMD patients who experience at least one psychological comorbidity is as high as 75% [6]. TMD is caused by dysfunction of the muscles of mastication and/or the temporomandibular joint (TMJ) itself, and can lead to symptoms such as pain, joint noises, impaired jaw function, and locking. This condition can be hard to diagnose, and even harder to treat, as the manifestations of TMD are varied. TMD patients may present overlapping symptoms with other chronic pain conditions, including headache, fibromyalgia, and neurological conditions. The mechanism of this is not certain, but is likely through the phenomenon of central sensitization, such as allodynia and hyperalgesia [7][8][9][10]. There are numerous established methods of diagnosing TMD, although none have a 100% success rate. There are also numerous established therapeutic methods for treating TMD, with more being proposed every year, as this research will demonstrate; however, no therapeutic method demonstrates a satisfactorily high rate of success.
Currently, the “gold standard” for TMD diagnosis is a Magnetic Resonance Imagine (MRI) scan; however, many patients will suffer from TMD despite no obvious pathological or mechanical disruptions [11]. Thus, TMD can be divided into three groups. Group I includes TMD caused by muscle disorders, including myofascial pain with and without limitations in mouth opening. Group II includes TMD caused by disc displacement with or without reductions and limitations in mouth opening. Group 3 includes arthralgia, arthritis, and arthrosis [12].

2. Novel Diagnostic Approaches to Temporomandibular Dysfunction

2.1. Novel Artificial Neural Network for TMD Diagnosis

At this time, artificial intelligence (AI) is primarily used within the medical field to aid in the diagnosis and treatment of life-threatening conditions such as cardiovascular disease and cancer. Although TMD has a similar prevalence to these conditions in the general population, the use of artificial intelligence for the diagnosis and treatment of TMD is still in its infancy. While TMD is not itself a life-threatening condition, TMD can present with similar symptoms to life-threatening conditions. In fact, 4% of acute myocardial infarctions present with pain in the craniofacial structures as the only symptom [13]. The complexity of diagnosing TMD, in conjunction with the fact that many orofacial pain symptoms arise from other parts of the body, make proper TMD diagnosis a significant challenge for the general practitioner.
Given the successful use of AI for the diagnosis and treatment of other areas of medicine, Kreiner et al. attempted to develop an algorithm to diagnose orofacial pain and TMD with equal or higher accuracy than a general dentist [13]. Kreiner et al. created an artificial neural network (ANN) which is a subset of AI. This program allows the input of multiple pieces of information (patient symptoms, diagnostic imaging, etc.) and creates an output (diagnosis). The Kreiner ANN was given the same patient scenarios as 12 general dentists and asked to determine whether the patient’s pain was of orofacial origin, and if so, to properly diagnose the condition. The neural network outperformed the dentists on average. The neural network was clearly superior at diagnosing pain from outside the orofacial region (e.g., referred cardiac pain, neuropathic pain). For example, only 25% of clinicians could diagnose the cases of referred orofacial pain from myocardial infarctions. The clinicians frequently chose diagnoses of “occlusal trauma”, “bruxism”, “periodontal disease”, and “I do not know” instead. Only two clinicians could accurately diagnose the patient suffering from migraine symptoms. Only half of the clinicians correctly diagnosed TMD, while the ANN was able to correctly identify all cases. For pain of odontogenic origin (e.g., pulpitis), there was no significant difference between the ANN and the general dentists.
This study found that the novel ANN showed high diagnostic accuracy for the diagnosis of TMD. The results showed that the ANN had a sensitivity of 96.9% and a specificity of 95.5% for the diagnosis of TMD. These results indicate that the ANN was highly accurate in identifying patients with TMD and distinguishing them from patients without TMD. This level of accuracy was found to be comparable to or better than other diagnostic tools currently used for TMD diagnosis, such as clinical examination and imaging.
The results suggest that the ANN could be a useful tool for the diagnosis of orofacial pain and TMD. The ANN has several advantages over traditional diagnostic tools, including the ability to quickly and accurately analyze large amounts of data and identify patterns and relationships that might be missed by human observers. Further research could focus on improving the ANN’s diagnostic algorithms and exploring other potential applications for ANN technology in dentistry and medicine.
Overall, this study demonstrates the promise of novel diagnostic tools using artificial intelligence. A simple neural network with only five layers of coding was able to outperform a dozen clinicians on diagnoses ranging from TMD to migraines to referred cardiac pain. More testing is needed before drawing conclusions about the widespread applicability of this ANN, and more AI algorithms like it. However, this is an area that contains vast potential for simplifying and streamlining the otherwise complicated task of accurately diagnosing patients with TMD.

2.2. Salivary Endocannabinoid Profiles

Each individual possesses a unique endocannabinoid (eCB) profile within their saliva. It has been suggested that this eCB profile may indicate the presence of underlying conditions that cause pain, such as temporomandibular disorder. The eCB profile of patients diagnosed with certain orofacial pain disorders has not been thoroughly studied. A study by Heiliczer et al. attempted to classify certain eCB profiles according to patients with current diagnoses of post-traumatic neuropathy, trigeminal neuralgia, temporomandibular disorders, migraine, tension-type headaches, and burning mouth syndrome [14]. Correlation analyses between eCB levels, a current and specific diagnosis, and pain characteristics were conducted.
Heiliczer et al. suggest that these findings could have several clinical implications. For example, salivary endocannabinoid profiles could be used as a diagnostic tool for chronic orofacial pain and headache disorders. Additionally, the findings suggest that endocannabinoid-based therapies, such as cannabinoid receptor agonists or inhibitors of endocannabinoid degradation, could be effective in treating these conditions. Heiliczer et al. also noted several limitations of the study, including the relatively small sample size and the lack of longitudinal data. Future studies could address these limitations by enrolling larger cohorts and following patients over time to assess the long-term effectiveness of endocannabinoid-based therapies.
Overall, the study suggests that salivary endocannabinoid profiles could be a useful tool for the diagnosis and management of chronic orofacial pain and headache disorders. The findings also support the potential therapeutic value of endocannabinoid-based therapies in these conditions. Further research is needed to confirm these findings and to explore the underlying mechanisms of endocannabinoid signaling in chronic pain and headache disorders. The fact that salivary samples of patients with certain orofacial pain disorders demonstrated signature eCB patterns suggests that more research should be conducted in this field. The potential to elucidate a certain eCB marker that correlates with temporomandibular disorder exists and would aid in the diagnosis of TMD patients going forward.

2.3. Signal Analysis to Diagnose TMJ Hypermobility

Frequently, certain noises emanating from the temporomandibular joint (TMJ) lead patients and clinicians to assume that temporomandibular dysfunction (TMD) must be present. These noises often including clicking, popping, and crepitus, among others. These noises can occur during speaking, eating, yawning, and other daily activities. However, these noises do not always coincide with disorders, and can lead to misdiagnoses. In fact, the noises caused by TMJ hypermobility are often errantly assumed to be caused by TMD [15]. Grochala et al. conducted a study of noises emanating from the TMJ using a novel technique called signal analysis [16]. This is a non-invasive technique that uses an electronic stethoscope to record noises associated with the TMJ during the process of opening and closing.
Signal analysis is a powerful tool for diagnosing and monitoring TMJ disorders because it enables the objective measurement of joint movement and function. This can be especially useful in cases where clinical examination alone may be insufficient to diagnose or monitor the progression of the condition. Additionally, signal analysis can provide valuable insights into the underlying biomechanical mechanisms of TMJ disorders, which can inform the development of new treatments and interventions. By creating a database of certain signals unique to patients with TMD versus those with TMJ hypermobility, practitioners may be able to compare the sounds of undiagnosed patients with the signals unique to certain diagnoses, and more accurately diagnose new patients. This is an area of research that still needs extensive study and data collection before it can be definitively used as a diagnostic aid; however, the potential benefit exists.

2.4. A Novel MRI Scoring System for TMD Diagnosis

Of the many diagnostic tools used by clinicians to diagnose TMD, magnetic resonance imaging (MRI) is widely considered the gold standard [17]. Not only does this imaging modality confer a high level of resolution of hard and soft tissue structures in the TMJ, but it can also produce imaging of the joint in motion. However, MRI is only useful for diagnosis if there is a reliable system for assessing the imaging and relating it to a diagnosis. In 2018, Wurm et al. proposed a novel MRI-based scoring system to diagnose TMD. This system offers a standardized evaluation using three main variables that assess key relevant structural changes within the TMJ [18]. This system includes an assessment of the articular disc, the direction of disc luxation, and osseous joint alterations. Although this novel system has potential to be a useful diagnostic tool, the inter-rater reliability of the system has not been assessed.
The correlation between the MRI-based scores and clinical assessments of TMD severity was also evaluated. The clinical assessments included pain intensity, jaw opening, and joint sounds. The results showed a significant correlation between the MRI-based scores and all three clinical assessments, indicating that the scoring system was able to accurately reflect the severity of TMD. Willenbrock et al. noted that the new scoring system has several advantages over existing systems. For example, it is based on MRI, which enables the non-invasive assessment of TMJ abnormalities. Additionally, the system includes multiple categories of abnormalities, which provides a more comprehensive assessment of TMJ health. However, Willenbrock et al. also noted some limitations of the system. For example, the system requires specialized training to use, which may limit its accessibility to some clinicians. Additionally, the system may not be able to detect some types of TMJ abnormalities that are not visible on MRI scans.
In conclusion, Willenbrock et al.’s study concluded that the novel Wurm et al. scoring system is reliable enough to use as a tool in the process of diagnosing patients with suspected TMD. The high reliability and validity of the system suggest that it could be a useful tool for clinicians in diagnosing and managing TMDs. Further research is needed to validate the system in larger patient populations and to explore its potential clinical applications.

2.5. Novel Functional Indices of Masticatory Muscle Activity

It is well known that for muscle activity to occur, specific electrical signal pathways within the musculature must occur. This includes the muscles surrounding the TMJ during functional movements and at rest. The practice of measuring electromyography has been applied to diagnosing bruxism [19], tension-type headaches [20], Down syndrome [21], different occlusal features [22], motor neuron disease [23], and in TMD patients [24]. Ginszt et al. hypothesized that analyzing masticatory muscle activity in patients with signs of TMD using novel functional indices could aid in more accurate diagnoses [25]. This team conducted a study in which 78 women were divided equally into two groups based on an existing diagnosis of TMD or a healthy adult. In order to record the bioelectrical activity of facial musculature, surface electromyography was used. The bioelectric activity of the temporalis anterior, the superficial masseter, and anterior bellies of the digastric muscles was recorded during functional clenching, functional opening, opening, and at rest. The data collected were analyzed using a wavelet transformer to extract the time–frequency characteristics of the surface electromyography signals. Ginszt et al. developed three functional indices: the muscle activation index, muscle activity rhythm index, and muscle contraction force index.

3. Novel Therapeutic Approaches to Temporomandibular Dysfunction

A PubMed search using the inclusion and exclusion criteria described in the Introduction yielded very few results for novel therapeutic tools published since July 2020. In total, four papers will be reviewed, but the first two articles described below are of limited applicability, relevance, and/or reliability. They have been included in this research for the purpose of completeness.

Novel TMD Treatment Using Aromatherapy Massage with Lavender Oil

A study was published in the Journal of Craniofacial and Sleep Practice that investigated the effects of massage therapy on alleviating TMD pain symptoms. This therapy theoretically reduces pain via activation of the pain–gate pathway, stimulates the parasympathetic center, and re-establishes muscular length and flexibility, improves local blood circulation, and increases the production of endogenous opioids [26]. This area of study has not received extensive study, and there is not a large body of evidence supporting its efficacy.
Benli et al. conducted a randomized controlled trial to investigate the effects of aromatherapy massage with lavender oil on pain reduction and maximal mouth opening in patients with myogenous TMD compared with a control group. For this study, 90 patients were selected based on stringent eligibility criteria: 30 patients were placed in the test group, which received aromatherapy massage with lavender oil; 30 patients were placed in the placebo group, and received massage therapy with sweet almond oil; 30 patients were placed in the control group, and received no massage therapy. All patients abstained from taking analgesic medication during the trial. Efforts were made to adequately control for other variables; however, a detailed description of those measures is outside the scope of this research.
The findings indicated that the aromatherapy massage group showed significant differences compared with control and placebo groups in terms of maximal mouth opening and the evaluated pain parameters (as measured by visual analog scale). At the beginning of the trial, there was no difference in the two measurements between all groups. Immediately after the treatment, both groups that received aromatherapy massage demonstrated statistically significant improvements in pain reduction and maximal opening compared with the control group. The group that received lavender oil treatment demonstrated significant improvements compared with the placebo group that received almond oil. At two months post-procedure, both massage groups again demonstrated significant improvements compared with the control group. Similarly, the group that received lavender oil demonstrated more pain reduction and greater maximal opening than the almond oil group. However, the difference in results compared with the control group declined compared with measurements taken immediately after treatment. The limited results seemed to suggest that the beneficial effects of treatment waned after a short period of time. These results suggest that there may be merit to further investigation into the use of both massage therapy and use of lavender oil as adjunctive, conservative treatment for pain reduction and increased maximal opening in TMD patients.

4. Novel Manual Techniques in Masticatory Muscle Relaxation in TMD Treatment

A study was published in the International Journal of Environmental Research and Public Health that investigates the degree of relaxation of muscles of mastication achieved by manual release techniques. This study by Urbański et al. enrolled patients who are currently undergoing prosthetic treatment to relieve TMD with a dominant muscular component [27]. Sixty patients were randomly assigned to a group that received post-isometric relaxation treatment or a group that received myofascial release treatment. Both groups received ten treatment sessions and were assessed using surface electromyography measurements of the anterior temporal and masseter muscles as well as the intensity of spontaneous masticatory muscle pain assessed via the visual analog scale.
The results from the study demonstrated that both groups exhibited decreased electrical activity in the temporalis and masseter muscles after treatment. Both treatment groups also exhibited a significant drop in the intensity of spontaneous pain in the masticatory muscle group. There was no significant difference in results between the two treatment groups. Urbański et al. suggest that both post-isometric relaxation treatment and myofascial release treatment are appropriate adjunctive treatments for TMD patients receiving prosthetic treatment. The authors also discussed the mechanisms by which manual techniques may exert their therapeutic effects. They suggested that manual techniques may help to release tension and adhesions in the masticatory muscles, increase blood flow and oxygen supply to the muscles, and stimulate the release of endorphins and other pain-relieving substances.
Overall, Urbański et al. concluded that manual techniques can be a valuable adjunctive therapy in the treatment of TMDs. They suggested that manual techniques should be considered as part of a comprehensive treatment plan that includes patient education, stress management, and other therapies, such as physical therapy and pharmacological interventions. While this area of treatment demonstrates potential for certain patients, more research is recommended before definitively adopting this treatment modality for TMD patients.

This entry is adapted from the peer-reviewed paper 10.3390/life13091808

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