Gouty tophus presenting as an anterior cruciate ligament mass in the knee
Bibliographic record
Abstract
INTRODUCTION AND IMPORTANCE: Tophacious gout presenting at the anterior cruciate ligament (ACL) is extremely rare and difficult to differentiate from other intraarticular pathology. This is mainly due to conventional diagnostic tools, such as MRI, producing ambiguous results versus pigmented villonodular synovitis (PVNS) and ganglion cysts. CASE PRESENTATION: Here we report an individual in their late-20s with a gouty tophus located at the origin of the ACL in the knee. Urate crystals on the articular cartilage in all three compartments was noted as well as on the synovium. On advanced imaging with an MRI, a large mass was seen anteriorly in the notch surrounding the ACL and posterior cruciate ligament (PCL). The tophus was biopsied and excised arthroscopically with excellent results. CLINICAL DISCUSSION: An ACL mass in the knee has a very broad differential diagnosis. MRI imaging alone makes it very difficult to differentiate between PVNS and gout tophi yielding a pre-operative diagnostic challenge. Additionally, we review diagnostic challenges faced by other groups with similar cases, as well as their chosen treatment. CONCLUSION: Gouty tophi arising from the origin of the ACL are extremely rare and remain difficult to diagnose due to their ambiguous nature in conventional imaging. In this report, we clearly convey the disparity in the diagnostic protocol for this type of intraarticular pathology. Future research should look to develop a superior protocol for identifying these pathologies to improve diagnostic accuracy.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".