Round Cell Liposarcoma Presenting as an FDG-Positive Primary With an FDG-Negative Retroperitoneal Metastasis
Bibliographic record
Abstract
A 34-year-old man, who presented with a 10-month history of an enlarging right ankle mass histologically proven to be a round cell/myxoid liposarcoma, was referred for an F-18 FDG PET/CT scan, which showed a heterogenous FDG-positive primary in the ankle and a 1.2-cm, FDG-negative, retroperitoneal lipid-attenuating nodule. On a follow-up PET/CT scan done 1 year later, the retroperitoneal nodules had grown into an 11-cm mass, which became FDG-positive and was subsequently histologically confirmed to be a liposarcoma metastasis. We present the imaging characteristics of this highly unusual case and a possible histologic explanation for the false-negative retroperitoneal metastasis on the staging PET/CT scan.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".