Tibial intraneural ganglion cysts arising from the tibiofemoral joint: illustrative cases
Bibliographic record
Abstract
BACKGROUND: Intraneural cysts involving the tibial nerve in the knee region (popliteal fossa) are rare. According to the articular (synovial) theory, which posits a joint origin for this pathology, these cysts originate from either the superior tibiofibular joint (STFJ) or the tibiofemoral (knee) joint. As tibial intraneural cysts arising from the tibiofemoral joint remain poorly understood, the authors present 2 illustrative cases and a review of the world's literature on all tibial intraneural ganglion cysts in the knee region. OBSERVATIONS: Fourteen cases of tibial intraneural ganglion cysts arising from the tibiofemoral joint were identified in the literature. Different articular branch patterns were demonstrated, which could be explained by the varied, rich articular branch innervation at the knee. Favorable outcomes were observed in cases in which the articular branch had been disconnected and the cyst drained and were comparable to the outcomes seen in tibial intraneural ganglion cysts with an STFJ origin. LESSONS: Tibial intraneural cysts in the knee region can be subdivided by their joint of origin: the STFJ or the tibiofemoral joint. Those arising from the tibiofemoral joint originate from different areas of the joint and propagate in predictable patterns, with favorable outcomes following surgical intervention when the joint connection is identified and treated. The origin of tibial intraneural cysts from the tibiofemoral joint are more complex than those originating from the STFJ but seem to have similar propagation patterns and outcomes.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".