Temporomandibular Joint Lesions with Intracranial Extension: Illustrative Cases from a Systematic Review of the Literature and Our Institution
Bibliographic record
Abstract
BACKGROUND: Intracranially extending temporomandibular joint (TMJ) lesions may be radiologically misinterpreted as primary intracranial or skull base pathologies, leading to diagnostic delays or inappropriate management. PURPOSE: This systematic review aimed to characterize the clinical and imaging features of such TMJ lesions and evaluate the impact of radiologic misclassification. We also aimed to develop a diagnostic framework for when to consider an intracranially extending TMJ lesion, based on clinical and radiologic features. DATA SOURCES: A comprehensive search of MEDLINE, Scopus, and EMBASE, conducted in accordance with PRISMA guidelines, yielded 2255 records. STUDY SELECTION: After screening with predetermined inclusion and exclusion criteria, 128 studies involving 152 patients were included in the final analysis. DATA ANALYSIS: Statistical analyses were performed using STATA software. We also identified 3 patient cases through our institutional neuroradiology practice who were clinically and radiologically assessed for intracranially extending TMJ lesions. DATA SYNTHESIS: Patients had symptoms for an average of 34 months before diagnosis (47% women, mean age 50 years). The most common pathologies were pigmented villonodular synovitis/tenosynovial giant-cell tumor (43%) and synovial chondromatosis (24%). Neurologic symptoms were reported in 48% of cases, most frequently hearing loss (70%). Nearly one-third (33%) of cases with an imaging differential did not list a TMJ pathology (18/55). In cases with accurate imaging diagnosis, 90% had both CT and MRI performed. Most lesions were nonenhancing (CT 83%, MRI 75%) and demonstrated no adjacent brain edema (96%). In 2 cases, a TMJ ganglion cyst and pseudogout were misdiagnosed as intracranial tumors, resulting in unnecessary intervention, including repeat craniotomy and radiotherapy. LIMITATIONS: There were inherent biases of case report literature, including variability in the reporting of the imaging and clinical features, management, and follow-up. CONCLUSIONS: TMJ lesions with intracranial extension often present with nonspecific symptoms and can mimic extra-axial tumors, leading to misdiagnosis on imaging. Recognition of hallmark imaging features, including lack of parenchymal invasion and distinct imaging patterns, may help improve radiologic accuracy and prevent overtreatment. We propose a diagnostic framework outlining when to suspect intracranially extending TMJ lesions based on clinical and imaging features, and how to avoid common diagnostic pitfalls.
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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 | 0.003 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.028 | 0.031 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".