Evaluation of the reproducibility in the interpretation of magnetic resonance images of the temporomandibular joint

MRI changes and clinical characteristics in temporomandibular joints with displacement of the articular disk without reduction - a cross-sectional observational study

OBJECTIVES

This study examined changes in magnetic resonance imaging (MRI) of temporomandibular joints (TMJ) with anterior displacement disk without reduction (DDwoR) and its correlation to clinical symptoms.

METHODS

190 individuals with DDwoR were evaluated according to Diagnostic Criteria for Temporomandibular Disorders (DC/TMD) and MRI. Pain's chronicity/intensity and limited mouth opening (locking) were correlated with: TMJ degeneration (MRI T1), effusion (T2), disc's shape and position (proton density).

RESULTS

In 103 TMJ with DDwoR, hemiconvex shape (41.6%), sclerosis (45.6%) and mild effusion (47.6%) were the most prevalent findings. There was not association (p > .05) between: different DDwoR positions with pain's intensity/chronicity; effusion with locking. Disk deformation was associated with degeneration (p = .034) and pain's intensity (p = .006). Locking was associated with degeneration (p = .05).

CONCLUSIONS

Condylar osteodegeneration is often related to DDwoR. Locking by DDwoR is associated with severe levels of chronic pain and articular disk deformation.

Detecting the articular disk in magnetic resonance images of the temporomandibular joint using YOLO series

The purpose of this study was to construct an artificial intelligence object detection model to detect the articular disk from temporomandibular joint (TMJ) magnetic resonance (MR) images using YOLO series. The study included two experiments using datasets from different MR imaging machines. A total of 536 MR images were retrospectively examined. The performance of YOLOv5 and YOLOv8 in detecting the TMJ articular disk in both normal and displaced conditions was evaluated. The impact of image-processing techniques, such as histogram equalization (HE) and contrast-limited adaptive HE (CLAHE) on model performance, was also examined. The results showed that the YOLO series could detect the articular disk regardless of displacement, with superior performance on images of normal disk position. The results suggest the applicability of object detection models in improving the diagnosis of TMJ disorders.

Evaluation of temporomandibular joint disc displacement with MRI-based radiomics analysis

OBJECTIVES

The purpose of this study was to propose a machine learning model and assess its ability to classify temporomandibular joint (TMJ) disc displacements on MR T1-weighted and proton density-weighted images.

METHODS

This retrospective cohort study included 180 TMJs from 90 patients with TMJ signs and symptoms. A radiomics platform was used to extract imaging features of disc displacements. Thereafter, different machine learning algorithms and logistic regression were implemented on radiomics features for feature selection, classification, and prediction. The radiomics features included first-order statistics, size- and shape-based features, and texture features. Six classifiers, including logistic regression, random forest, decision tree, k-nearest neighbours (KNN), XGBoost, and support vector machine were used for a model building which could predict the TMJ disc displacements. The performance of models was evaluated by sensitivity, specificity, and ROC curve.

RESULTS

KNN classifier was found to be the most optimal machine learning model for prediction of TMJ disc displacements. The AUC, sensitivity, and specificity for the training set were 0.944, 0.771, 0.918 for normal, anterior disc displacement with reduction (ADDwR) and anterior disc displacement without reduction (ADDwoR) while testing set were 0.913, 0.716, and 1 for normal, ADDwR, and ADDwoR. For TMJ disc displacements, skewness, root mean squared, kurtosis, minimum, large area low grey level emphasis, grey level non-uniformity, and long-run high grey level emphasis, were selected as optimal features.

CONCLUSIONS

This study has proposed a machine learning model by KNN analysis on TMJ MR images, which can be used for TMJ disc displacements.

Influence of examiner calibration on clinical and MRI diagnosis of temporomandibular joint disc displacement: a systematic review and meta-analysis

OBJECTIVES

This study aimed to verify the accuracy of clinical protocols for the diagnosis of disc displacement (DD) compared with MRI, considering examiners' calibration.

METHODS

PubMed, Cochrane (Central), Scopus, Web of Science, LILACS, Embase, Science Direct, Google Scholar, and DANS EASY Archive databases were searched. Two reviewers independently screened and selected the studies. A meta-analysis was conducted using the R Statistical software. Results are shown using sensitivity and specificity, and 95% confidence intervals.

RESULTS

Of the 20 studies included in the systematic review, only three were classified as low risk of bias. Seventeen studies were included in the meta-analysis. Compared to MRI, clinical protocols showed overall sensitivity and specificity of 0.75 (0.63-0.83) and 0.73 (0.59-0.84) for DD diagnosis, respectively. For DD with reduction, sensitivity was 0.64 (0.48-0.77) and specificity was 0.72 (0.48-0.87). For DD without reduction, sensitivity was 0.58 (0.39-0.74) and specificity 0.93 (0.83-0.97). Only 8 studies reported examiner calibration when performing clinical and/or MRI evaluation; nevertheless, calibration showed a tendency to improve the diagnosis of DD.

CONCLUSION

The sensitivity and specificity of clinical protocols in the diagnosis of DD are slightly below the recommended values, as well as the studies lack calibration of clinical and MRI examiners. Examiner calibration seems to improve the diagnosis of DD.

Image preprocessing with contrast-limited adaptive histogram equalization improves the segmentation performance of deep learning for the articular disk of the temporomandibular joint on magnetic resonance images

OBJECTIVES

The objective was to evaluate the robustness of deep learning (DL)-based encoder-decoder convolutional neural networks (ED-CNNs) for segmenting temporomandibular joint (TMJ) articular disks using data sets acquired from 2 different 3.0-T magnetic resonance imaging (MRI) scanners using original images and images subjected to contrast-limited adaptive histogram equalization (CLAHE).

STUDY DESIGN

In total, 536 MR images from 49 individuals were examined. An expert orthodontist identified and manually segmented the disks in all images, which were then reviewed by another expert orthodontist and 2 expert oral and maxillofacial radiologists. These images were used to evaluate a DL-based semantic segmentation approach using an ED-CNN. Original and preprocessed CLAHE images were used to train and validate the models whose performances were compared.

RESULTS

Original and CLAHE images acquired on 1 scanner had pixel values that were significantly darker and with lower contrast. The values of 3 metrics-the Dice similarity coefficient, sensitivity, and positive predictive value-were low when the original MR images were used for model training and validation. However, these metrics significantly improved when images were preprocessed with CLAHE.

CONCLUSIONS

The robustness of the ED-CNN model trained on a dataset obtained from a single device is low but can be improved with CLAHE preprocessing. The proposed system provides promising results for a DL-based, fully automated segmentation method for TMJ articular disks on MRI.

MRRead-A Novel Approach to Training Residents in Magnetic Resonance Image Temporomandibular Joint Interpretation

PURPOSE

The purpose of our study was to create an online, web-based training module that would instruct a group of participants in the interpretation of a magnetic resonance image (MRI) of the temporomandibular joint (TMJ) scan in a logical, step-wise manner to locate and identify all relevant features of internal derangement. The investigator's hypothesis was that implementing the MRRead TMJ training module would improve the participants' competency in the interpretation of MRI TMJ scans.

METHODS

The investigators designed and implemented a single-group prospective cohort study. The study population was composed of oral and maxillofacial surgery interns, residents, and staff. Subjects eligible for study inclusion were oral and maxillofacial surgeons of any level, between 18 and 50 years of age, that completed the MRRead training module to completion. The primary outcome variable was the difference between the pretest and post-test scores of the participants, and the frequency of missing internal derangement findings before and after the course. Secondary outcomes of interest were subjective data gathered from the course, including participant feedback as well as subjective evaluation of the training module and perceived benefit, as well as the learner's self-reported confidence level in interpreting MRI TMJ scans on their own before and after completion of the course. Descriptive and bivariate statistics were used.

RESULTS

The study sample consisted of 68 subjects, aged 20 to 47 (M = 29.1) years. When comparing the results of the exams precourse and post course, the overall frequency of missed features of internal derangement decreased from 19.7 to 5.9, and the total score overall increased from 8.5 to 68.6%. Regarding secondary outcomes, the majority of participants indicated that they agree or strongly agree with a number of positive subjective questions asked. In addition, there was a statistically significant increase in the participants' comfort levels in the interpretation of MRI TMJ scans.

CONCLUSION

The results of this study confirm the hypothesis that completing the MRRead training module (www.MRRead.ca) improves competency and comfort among participants in the interpretation of MRI TMJ scans and their identification of features of internal derangement correctly.

Automated segmentation of articular disc of the temporomandibular joint on magnetic resonance images using deep learning

Temporomandibular disorders are typically accompanied by a number of clinical manifestations that involve pain and dysfunction of the masticatory muscles and temporomandibular joint. The most important subgroup of articular abnormalities in patients with temporomandibular disorders includes patients with different forms of articular disc displacement and deformation. Here, we propose a fully automated articular disc detection and segmentation system to support the diagnosis of temporomandibular disorder on magnetic resonance imaging. This system uses deep learning-based semantic segmentation approaches. The study included a total of 217 magnetic resonance images from 10 patients with anterior displacement of the articular disc and 10 healthy control subjects with normal articular discs. These images were used to evaluate three deep learning-based semantic segmentation approaches: our proposed convolutional neural network encoder-decoder named 3DiscNet (Detection for Displaced articular DISC using convolutional neural NETwork), U-Net, and SegNet-Basic. Of the three algorithms, 3DiscNet and SegNet-Basic showed comparably good metrics (Dice coefficient, sensitivity, and positive predictive value). This study provides a proof-of-concept for a fully automated deep learning-based segmentation methodology for articular discs on magnetic resonance images, and obtained promising initial results, indicating that the method could potentially be used in clinical practice for the assessment of temporomandibular disorders.

Subjective analysis of the application of enhancement filters on magnetic resonance imaging of the temporomandibular joint

OBJECTIVE

The aim of this study was to investigate the effect of enhancement filters on magnetic resonance imaging (MRI) of the temporomandibular joint (TMJ).

STUDY DESIGN

In total, 66 MRI scans of the TMJ were analyzed without filtration and with the application of 2 filters: Sharpen 1 and Sharpen 2 (OnDemand software). Two dentomaxillofacial radiologists examined the original and filtered images individually. Intra- and interobserver concordance was measured by using generalized estimating equations. The observers evaluated the subjective image quality and the visibility of 3 components of the TMJ: disk, condyle, and articular eminence. The images were ranked on a 4-point scale, from poor to excellent. The image quality of all filtered images was compared by using the χ² test and Bonferroni correction for multiple comparisons.

RESULTS

Intra- and interobserver concordance was good. The images filtered with Sharpen 1 and Sharpen 2 provided better definition of the structures compared with nonfiltered images, providing the highest scores for subjective image quality for all structures (P < .0001).

CONCLUSIONS

The use of enhancement filters led to improved subjective quality and may improve the diagnostic efficacy of MRI in TMJ evaluation.

MRI alone versus MRI-CBCT registered images to evaluate temporomandibular joint internal derangement

OBJECTIVE

To evaluate the effect of magnetic resonance imaging-cone beam computed tomography (MRI-CBCT) image registration on inter- and intraexaminer consistency when evaluating temporomandibular joint (TMJ) internal derangement compared to MRI alone.

METHODS

MRI and CBCT images of 25 patients (50 TMJs) were obtained and coregistered using mutual-information rigid image registration via Mirada XD software. Two experienced radiologists independently and blindly evaluated two types of images (MRI alone and MRI-CBCT registered images) at two different times (T1 and T2) for TMJ internal derangement, based on sagittal and coronal articular disc position in relation to the head of the condyle and the posterior slope of the articular eminence.

RESULTS

The intraexaminer consistency with MRI alone (examiner 1 = 0.85 [0.74-0.92]; examiner 2 = 0.91 [0.84-0.95]) was lower than for the MRI-CBCT registered images (examiner 1 = 0.95 [0.91-0.97]; examiner 2 = 0.97 [0.96-0.99]). The interexaminer consistency of evaluating internal derangement with MRI alone (0.52 [0.18-0.73] at T1; 0.71 [0.45-0.84] at T2) was lower than for the MRI-CBCT registered images (0.97 [0.95-0.98] at T1; 0.98 [0.96-0.99] at T2). When disc position classification was dichotomized to normal versus anteriorly displaced, intraexaminer agreement for the two examiners was 0.52 and 0.63 for MRI alone, but was 0.91 and 0.92 for MRI-CBCT registered images. Interexaminer agreement for MRI alone was 0.29 at T1 and 0.42 at T2, but was 0.96 at both examination times for MRI-CBCT registered images.

CONCLUSION

The MRI-CBCT registered images improved intra- and interexaminer consistency in the evaluation of internal derangement of TMJ.

Web-based calibration of observers using MRI of the temporomandibular joint

OBJECTIVES

Research diagnostic criteria for temporomandibular disorders (RDC/TMDs) were proposed in 1992 with the aim of standardizing and testing methods for diagnosing TMDs. RDC/TMDs have so far been lacking standardized methods for imaging and criteria for imaging diagnosis of disorders of the temporomandibular joint (TMJ). Criteria for disorders of the TMJ have recently been proposed for MRI. The aim of this study was to publish MR images of the TMJ on the web and to test the agreement of five observers using the criteria.

METHODS

20 cases of MRI of the TMJ were published on the web together with the criteria. The MR images were taken in closed and open mouth positions, and sagittal and coronal views. Five observers diagnosed disc position, disc shape, joint effusion and loose calcified bodies in the TMJ.

RESULTS

In all cases except one, three or more observers agreed upon the diagnosis. All agreed on whether a loose calcified body was present or not. The second best agreement was obtained for disc position in the sagittal view, where all observers agreed in 16 of the 20 cases. For disc position in the coronal view and the evaluation of the disc shape, observer agreement was lower.

CONCLUSION

Criteria were useful in order to standardize and simplify evaluation and thereby probably increase the diagnostic outcome among different observers for MRI of the TMJ. We recommend that the criteria be used internationally to facilitate comparisons between different studies.

Evaluation of the correlation between disc displacements and degenerative bone changes of the temporomandibular joint by means of magnetic resonance images

The aim was to evaluate the correlation between disc displacements and degenerative bone changes in magnetic resonance images (MRI) of 112 patients of both genders, with signs and symptoms of temporomandibular disorder. For this purpose, a calibrated examiner evaluated 224 MRI by assigning scores for the displacement of the disc and degenerative bone changes. Disc displacement was found in 58.42% of the temporomandibular joints (TMJs) evaluated. Anterior displacement of the disc with reduction was the most common, occurring in 67.18% cases of joints with disc displacement. Degenerative bone changes were observed in 53.94% of the TMJs analysed. There was significant correlation between disc displacement with reduction and condylar flattening, disc displacement without reduction and condylar flattening, disc displacement without reduction, and associated degenerative bone changes (flattening and erosion, flattening, osteophyte and erosion; flattening and osteophytes, erosion and sclerosis, flattening and sclerosis, flattening, osteophytes and sclerosis). The correlation between advanced cases of disc displacement and the occurrence of degenerative bone changes emphasises the importance of MRI for an accurate diagnosis and development of an appropriate treatment plan and in cases in which clinical examination is not sufficient for these purposes.

The impact of imaging technologies on temporomandibular joint disorder diagnosis

DATA SOURCES

Medline, the Cochrane Library databases and reference list of review articles were searched.

STUDY SELECTION

Three examiners selected publications. To be included the publication had to elucidate the diagnostic thinking efficacy and/or therapeutic efficacy of MRI and/or CT in the diagnosis of disc displacement, inflammatory disorders (capsulitis, synovitis) and osteoarthrosis of the temporomandibular joint (TMJ). Publications related to trauma, tumours, systemic diseases, synovial chondromatosis; cadaver studies; narrative literature reviews; and studies of other TMJ imaging methods were excluded.

DATA EXTRACTION AND SYNTHESIS

Data were extracted by three examiners with disputes being settled by consensus. Study quality was assessed using the QUADAS tool.(1) No synthesis was performed as only one study was identified.

RESULTS

One study was judged relevant. This study evaluated evidence of the efficacy of MRI in the diagnosis of disc position and configuration, disc perforation, joint effusion, and osseous and bone marrow changes in the temporomandibular joint, but no publication reported diagnostic thinking efficacy or therapeutic efficacy.

CONCLUSIONS

The absence of studies on the therapeutic efficacy of MRI and CT on TMJD reinforces the need for investment in decision-making studies; meanwhile, sectional imaging tests should be prescribed with caution, especially when health budgets are limited.