Infrared thermography assessment of patients with temporomandibular disorders

Accuracy of the Fonseca Anamnestic Index for identifying pain-related and/or intra-articular Temporomandibular Disorders

Objectives: This study established the diagnostic accuracy of the Fonseca Anamnestic Index (FAI) in relation to the Diagnostic Criteria for TMD (DC/TMD) standard.Methods: A total of 866 TMD patients and 57 TMD-free controls were instructed to answer the FAI and DC/TMD Symptom Questionnaire (SQ). Participants were subsequently categorized into no (NT), pain-related (PT), and/or intra-articular (IT) TMDs using the DC/TMD protocolized examination/algorithms. Receiver operating characteristics (ROC) curves, best cut-off points, and accuracy measures were determined.Results:The FAI demonstrated high accuracy for detecting all TMDs, PT, and IT (AUC = 0.96-0.98). The best cut-off points were 22.50 for all TMDs/IT and 27.50 for PT. Sensitivity of the FAI was high (94.23-98.21%), but specificity was moderate (87.72%) for all diagnostic categories.Discussion:The diagnostic accuracy of the FAI for identifying pain-related and intra-articular TMDs was high. FAI scores ≥25 points should be used to screen for TMDs.

Thermal profile classification of the back of sportive and sedentary healthy individuals

BACKGROUND

Infrared thermography (IRT) is a non-harmful, risk-free imaging technique and it has application for healthy and pathological population.

OBJECTIVE

The aim of this study is to evaluate the thermographic profiles of the back of sport practitioners from different disciplines and compare it with those of sedentary healthy individuals.

METHOD

The back of 160 healthy subjects were evaluated, and participants were grouped considering their sport practice: team sport (TS), individual sport (IS), weight training (WT), inactive (I). Three regions of interest were identified to analyze the cervical, thoracic and lumbar temperatures of the back.

RESULTS

The Multivariate analysis of variance (MANOVA) resulted significant showing statistical differences for the cervical (p < 0.001), dorsal (p = 0.0011), and lumbar areas (p = 0.0366). The Tukey post-hoc test for pairwise comparison showed statistically significant differences between groups. For the cervical area significance was found between the IN and WT group (p = 0.002), the IN and IS group (p < 0.001), IN and TS group (p = 0.020). The dorsal area resulted significant between the IN and WT group (p = 0.007), the IN and IS group (p < 0.001), IN and TS group. The lumbar area showed significant differences only between the IN and WT group and the IN and IS group (p = 0.043).

CONCLUSION

This study demonstrated that inactive individuals manifest a statistically significant higher temperature in the cervical, dorsal and lumbar area of the back compared to sportive individuals.

Thermographic examination of gingival phenotypes: correlation between morphological and thermal parameters

OBJECTIVES

To evaluate the clinical and thermographic aspects of the gingival phenotype (GP) in healthy subjects.

MATERIALS AND METHODS

The study sample examined 264 teeth, upper and lower incisors, comprising 132 central incisors (CI) and 132 lateral incisors (LI), in 33 healthy volunteers. Four periodontal parameters were recorded systematically: ratio of width to length of the dental crown (CW/CL), height of the gingival attachment (KGW), probing depth (PD), and gingival transparency (GT). The temperatures of the attached gingiva (KGW temp) and the free gingival margin (FGM Temp) were also recorded by way of infrared thermography (IRT).

RESULTS

The average age of the sample was 30.70 ± 7.65 years. Of the 264 teeth evaluated, 76.1% had a thin GP. There was a significant association between CW/CL (p < 0.001), KGW (p < 0.001), PD (p < 0.007), and FGM Temp (p < 0.006) with the tooth groups. The results show a significant and inversely proportional correlation between clinical parameters and gingival temperature (p < 0.05). A significant association was found between CW/CL (p < 0.026); KGW (p < 0.001); and GP.

CONCLUSION

CW/CL, KGW, PD, and FGM Temp vary according to tooth group. The majority of the sample presented with the thin GP, which was more prevalent in the lower LIs and CIs. No significant association could be observed between thermographic parameters and GP.

CLINICAL RELEVANCE

Knowledge of the temperature of the gingival tissues can be useful in helping to diagnose and plan periodontal treatments. Moreover, our findings will help future studies evaluate the use of IR as an auxiliary diagnostic method in dentistry, eliminating GP as a confounding factor, since it does not seem to influence the temperature of the gingival tissues.

Gingivectomy with high-power laser for correction of the gummy smile resulting from altered passive eruption-a case series

To compare the efficacy between the surgical techniques of gingivectomy with high-power laser (HPL) and conventional gingivectomy for correction of a gummy smile (GS) due to altered passive eruption (APE). This was a case series of six female patients diagnosed with GS associated with APE. For the conventional gingivectomy procedure and for the one using the diode laser (808 nm, 2 W, in continuous mode), the six upper anterior teeth were divided into two groups (control (CG)-# 11, # 12, # 13, and test (TG)-# 21, # 22, # 23). Analyses of intraoperative bleeding and levels of pain and postoperative tissue repair were performed. The thermal pattern analysis was performed using infrared thermography. The level of significance was set at p < 0.05. There was no intraoperative bleeding in the TGs (p = 0.002). The CG showed tissue repair significantly better than the TG on the 14th postoperative day (p = 0.004). There were no statistically significant differences regarding the level of postoperative pain between the groups (p > 0.05). Regarding the thermographic analysis, there were also no statistically significant differences (p > 0.05). HPL gingivectomy was more effective, regarding the absence of intraoperative bleeding, while the conventional technique promoted better tissue repair. No significant differences were observed in the other parameters, possibly due to the minimal damage caused by gingivectomy, with either HPL or the conventional procedure, as there was no removal of bone tissue.

Artificial intelligence and infrared thermography as auxiliary tools in the diagnosis of temporomandibular disorder

OBJECTIVE

To assess three machine learning (ML) attribute extraction methods: radiomic, semantic and radiomic-semantic association on temporomandibular disorder (TMD) detection using infrared thermography (IT); and to determine which ML classifier, KNN, SVM and MLP, is the most efficient for this purpose.

METHODS AND MATERIALS

78 patients were selected by applying the Fonseca questionnaire and RDC/TMD to categorize control patients (37) and TMD patients (41). IT lateral projections of each patient were acquired. The masseter and temporal muscles were selected as regions of interest (ROI) for attribute extraction. Three methods of extracting attributes were assessed: radiomic, semantic and radiomic-semantic association. For radiomic attribute extraction, 20 texture attributes were assessed using co-occurrence matrix in a standardized angulation of 0°. The semantic features were the ROI mean temperature and pain intensity data. For radiomic-semantic association, a single dataset composed of 28 features was assessed. The classification algorithms assessed were KNN, SVM and MLP. Hopkins's statistic, Shapiro-Wilk, ANOVA and Tukey tests were used to assess data. The significance level was set at 5% (p < 0.05).

RESULTS

Training and testing accuracy values differed statistically for the radiomic-semantic association (p = 0.003). MLP differed from the other classifiers for the radiomic-semantic association (p = 0.004). Accuracy, precision and sensitivity values of semantic and radiomic-semantic association differed statistically from radiomic features (p = 0.008, p = 0.016 and p = 0.013).

CONCLUSION

Semantic and radiomic-semantic-associated ML feature extraction methods and MLP classifier should be chosen for TMD detection using IT images and pain scale data. IT associated with ML presents promising results for TMD detection.

Facial Paralysis Detection in Infrared Thermal Images Using Asymmetry Analysis of Temperature and Texture Features

Facial temperature distribution in healthy people shows contralateral symmetry, which is generally disrupted by facial paralysis. This study aims to develop a quantitative thermal asymmetry analysis method for early diagnosis of facial paralysis in infrared thermal images. First, to improve the reliability of thermal image analysis, the facial regions of interest (ROIs) were segmented using corner and edge detection. A new temperature feature was then defined using the maximum and minimum temperature, and it was combined with the texture feature to represent temperature distribution of facial ROIs. Finally, Minkowski distance was used to measure feature symmetry of bilateral ROIs. The feature symmetry vectors were input into support vector machine to evaluate the degree of facial thermal symmetry. The results showed that there were significant differences in thermal symmetry between patients with facial paralysis and healthy people. The accuracy of the proposed method for early diagnosis of facial paralysis was 0.933, and the area under the ROC curve was 0.947. In conclusion, temperature and texture features can effectively quantify thermal asymmetry caused by facial paralysis, and the application of machine learning in early detection of facial paralysis in thermal images is feasible.

Thermography as a Method to Detect Dental Anxiety in Oral Surgery

(1) Background: the aim of this study was to evaluate if dental anxiety can be measured objectively using thermal infrared imaging. (2) Methods: Patients referred to the Department of Oral Surgery of the University of Naples Federico II and requiring dental extractions were consecutively enrolled in the study. Face thermal distribution images of the patients were acquired before and during their first clinical examination using infrared thermal cameras. The data were analyzed in relation to five regions of interest (ROI) of the patient’s face (nose, ear, forehead, zygoma, chin). The differences in the temperatures assessed between the two measurements for each ROI were evaluated by using paired T-test. The Pearson correlation and linear regression were performed to evaluate the association between differences in temperatures and Modified Dental Anxiety Scale (MDAS) questionnaire score, age, and gender; (3) results: sixty participants were enrolled in the study (28 males and 32 females; mean age 57.4 year-old; age range 18–80 year-old). Only for nose and ear zone there was a statistically significant difference between measurements at baseline and visit. Correlation between the thermal imaging measurements and the scores of the MDAS questionnaire was found for nose and ear, but not for all of the other regions. (4) Conclusions: the study demonstrated a potential use of thermal infrared imaging to measure dental anxiety.

Role of thermography in the assessment of temporomandibular disorders and other musculoskeletal conditions: A systematic review

The aim of this review was to evaluate whether thermal imaging may constitute a reliable assessment method of musculoskeletal and temporomandibular disorders (TMD/MSD). A systematic review was conducted in the Pubmed, Scopus, Cochrane library, Web of Science, and Lilacs databases. The search terms were "musculoskeletal disorders,""temporomandibular disorders,""infrared thermography,""thermography," and "infrared imaging." The inclusion criteria were: studies published between January 1985 and January 2021, performed in humans, with sample size equal or greater than 20 patients, written in English, Portuguese, French and/or Spanish, and full text available. The exclusion criteria were: systematic reviews, case studies, and/or studies focused on pathologies beyond the review's domain. The risk of bias was evaluated using CASP 2018. A total of 2032 articles were retrieved. Of these, 25 studies met the inclusion criteria and were included to withdraw the following information: title, type of study, first author and year of publication, objective, number of participants, comparisons, and principal conclusions. No RCT were found. Despite some disparity, points of convergence among the majority of authors could be found. In general, healthy individuals show subtle thermal differences between contralateral homolog areas. Concerning orofacial structures, unilateral symptomatic individuals may show thermal differences equal or greater than 0.4°C. Infrared thermography accuracy in diagnosing TMD/MSD is still considered low to moderate. Despite some limitations, IRT might constitute a valuable supporting diagnostic tool in the medical field of TMD and MSD.

Diagnostic accuracy of the short-form Fonseca Anamnestic Index in relation to the Diagnostic Criteria for Temporomandibular Disorders

STATEMENT OF PROBLEM

Screening for temporomandibular disorders (TMDs) is important in research and clinical practice. The short-form Fonseca Anamnestic Index (SFAI) was recently introduced but had only been validated for muscle disorders.

PURPOSE

The purpose of this clinical study was to determine the diagnostic accuracy of the SFAI and its discrete and pooled items in relation to the Diagnostic Criteria for Temporomandibular Disorders (DC/TMD) benchmark.

MATERIAL AND METHODS

A total of 866 consecutive participants with TMDs and 57 TMD-free controls (aged ≥18 years) were recruited. The participants (n=923; mean age 32.8 ±13.3 years; women 79.2%) answered the FAI, and TMD diagnoses were derived based on the DC/TMD protocol and algorithms. The 5-item SFAI, which comprised 2 pain-related and 3 function-related TMD questions, was subsequently acquired and assessed with reference to the DC/TMD diagnoses. The receiver operating characteristics (ROC) was used to verify accuracy (area under the curve [AUC]) and the best cutoff points. Sensitivity, specificity, predictive values, and likelihood ratios were also examined.

RESULTS

Pain-related (PT) and intra-articular (IT) TMDs were present in 48.3% (446/923) and 82.7% (763/923) of the participants, respectively. The SFAI demonstrated high accuracy for identifying all TMDs, PT, and IT (AUC of 0.97, 0.99, and 0.97, respectively). The best cutoff points were 12.5 for all TMDs/IT and 17.5 for PT. Sensitivity of the SFAI ranged from 90.7% to 97.5% while specificity varied from 93.0% to 96.5%, with the highest values for PT. As positive predictive values (99.4% to 99.5%) were greater than negative ones (41.7% to 83.3%), the SFAI was better at detecting the presence than the absence of TMDs. With reference to PT, the sensitivity, and specificity of the 2 discrete and pooled pain-related questions (questions 3 and 4), extended from 82.3% to 99.3% and 77.2% to 96.5% respectively. With regard to IT diagnoses, sensitivity and specificity ranged from 56.0% to 98.3% and 86.0% to 98.3% for the 3 discrete and pooled function-related items (questions 1, 2, and 5).

CONCLUSIONS

The SFAI presented high degrees of diagnostic accuracy in relation to the DC/TMD and can be used for screening TMDs. SFAI scores between 15 and 50 points should be used to identify the presence of TMDs, with scores ≥20 points specifying possible pain-related TMDs.

Diagnosis of Temporomandibular Disorders Using Thermovision Imaging

Temporomandibular joint dysfunction (TMD) is a chronic disease of various etiologies. Correct TMD diagnosis enables to apply effective treatment and significantly improves the quality of patients' lives. One of the diagnostic methods subjected to evaluation in recent years is thermography, which enables safe, noninvasive, and quick imaging of the temperature distribution of temporomandibular joint-associated tissues. This paper, based on Medline, Dentistry & Oral Sciences Source, Academic Search Ultimate, Medline Complete databases, presents basic information related to thermovision imaging and outlines the direction of research conducted in recent years which fight with difficulties in the interpretation of thermograms that require specialized, dedicated analysis and processing of the obtained images. The problem concerns also no standardized protocol for measuring masticatory muscle temperature.