P.120 Intracranial extension of temporomandibular joint (TMJ) lesions: A review of neuroimaging and clinical features
Bibliographic record
Abstract
Background: Intracranial extension of temporomandibular joint (TMJ) lesions is uncommon and may lead to radiological misinterpretation. This review aimed to identify clinical and radiological features of these lesions and whether radiological misinterpretation contributed to delayed or incorrect intervention. Methods: A comprehensive search of MEDLINE, SCOPUS, and Embase identified 2,256 records. Studies with clinical and imaging details of TMJ lesions extending intracranially were included. Reviews and non-English studies were excluded. After screening, 113 studies involving 132 patients were included. Results: Patients had an average symptom duration of 32 months until diagnosis (47% female, mean age 50±15 years). The most common diagnoses were pigmented villonodular synovitis/tenosynovial giant cell tumor (46%) and synovial chondromatosis (24%). Neurological symptoms were reported in 48% of cases, most frequently hearing loss (35%). Diagnostic accuracy increased from 38% to 62% when both CT and MRI were used. Most lesions were non-enhancing on CT (85%) and MRI (74%), and demonstrated no edema (96%). In one case, a ganglion cyst was misdiagnosed as a cystic brain tumor, leading to neurosurgical resection. Conclusions: TMJ lesions extending intracranially have neurological symptoms in less than half of cases and demonstrate no enhancement or edema. Familiarity with these characteristics is essential to avoiding misdiagnoses and ensuring timely management.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.014 | 0.017 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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 source (direct Gemma or distilled Codex), 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".