Kikuchi-Fujimoto lymphadenitis imitating metastatic melanoma on positron emission tomography: a case report
Bibliographic record
Abstract
BACKGROUND: Accurate staging is critical for decision-making for the treatment of malignant conditions. Fluoro-deoxy-glucose positron emission tomography-computed tomography (FDG PET-CT) is a highly sensitive imaging modality for the assessment of distant metastases; however false positive results are possible due to its lower specificity with detection of other hypermetabolic pathologies. CASE PRESENTATION: A patient with high-risk thigh melanoma was staged with FDG PET-CT. Four ipsilateral inguinal nodes (three superficial, one deep) demonstrated intense hypermetabolic activity. Metastatic melanoma was confirmed in the largest superficial inguinal node with ultrasound-guided fine needle aspiration. Histopathology demonstrated metastatic melanoma in one superficial node and histiocytic necrotizing lymphadenitis, also known as Kikuchi-Fujimoto disease in five deep inguinal nodes. CONCLUSION: This case illustrates a false positive FDG PET-CT due to coincidental, synchronous melanoma and Kikuchi-Fujimoto disease in the same draining lymph node basin.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.004 | 0.003 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.008 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 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".