Diagnostic Value of Panoramic Radiographs in the Assessment of Degenerative Joint Disease: A Retrospective Study
Bibliographic record
Abstract
INTRODUCTION AND AIMS: This study evaluated the potential of panoramic radiographs (PR) for assessing temporomandibular joint (TMJ) osseous changes compared to Cone-beam Computed Tomography (CBCT). Our ultimate goal is to understand the value of PR as a screening tool and to get guidance for when CBCT should be requested for further investigation. METHODS: This cross-sectional retrospective study included patients 18 years or older with a PR and CBCT of TMJ from the School of Dentistry, University of Alberta, between 2021 and 2024. Exclusion criteria included poor image quality, an interval between PR and CBCT over 6 months, and TMJ not fully captured. Assessed findings from the images included condyle and articular eminence flattening, altered size, osteophyte formation, sclerosis, and erosion. Statistical analyses verified the diagnostic accuracy of PR in identifying TMJ degenerative findings compared to CBCT, the reference standard. RESULTS: One hundred and two TMJs from 51 patients (40 females and 11 males) were included in the study. PR sensitivity was below diagnostic thresholds recommended by current guidelines, ranging from 0 to 0.57, with only condyle flattening (0.55) and condyle altered shape/size (0.57), with a sensitivity above 0.50. A true negative was the most frequent score for all osseous findings except for flattening the condyle, with a high true positive in 32.25% of the cases. The specificity of PR ranged from 0.71 to 1.00. CONCLUSION: PR is an opportunistic screening tool but does not meet sensitivity thresholds to serve as a stand-alone diagnostic method for TMJ DJD. Abnormal findings seen in the PR should prompt CBCT to confirm osseous pathology. CLINICAL RELEVANCE: PR is widely used in dental practice and may reveal gross TMJ abnormalities. When these findings align with clinical signs or symptoms, CBCT should be considered for further assessment. This approach supports earlier detection of DJD while adhering to the ALADAIP principle.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".