Incidental thyroid “PETomas”: clinical significance and novel description of the self-resolving variant of focal FDG-PET thyroid uptake
Bibliographic record
Abstract
BACKGROUND: Recent series of incidental thyroid activity on fluorodeoxyglucose positron emission tomography (FDG-PET) in patients evaluated for nonthyroidal malignancy, which we refer to as a "PEToma," have suggested that such lesions are associated with a significant incidence of primary thyroid cancer. METHODS: We retrospectively reviewed 6457 FDG-PET scans performed on 4726 patients from May 2004 to March 2007. We reviewed the cases of patients whose PET or computed tomography (CT) radiology reports described PET uptake within the thyroid to identify incidence and malignant potential of PETomas and evaluate their clinical and histopathologic features. RESULTS: We found that 160 patients (3.4%) had incidental, abnormal FDG uptake in the thyroid gland, 103 of whom had focal uptake (the PEToma group). Of these patients, 50 (48%) underwent further investigations, including ultrasonography in 48, fine-needle aspiration cytology in 38 and computed tomography in 3. Ten patients underwent surgery, and papillary thyroid cancer was identified in 9. The remaining 53 patients with PETomas underwent no further investigation. Interestingly, 5 patients who had focal uptake within the thyroid showed either spontaneous resolution on repeat FDG-PET (self-resolving) or no focal lesion on subsequent ultrasonography (false-positive). CONCLUSION: The incidence of papillary thyroid cancer in the present series is similar to that in the literature. Although some patients will show self-resolving or false-positive focal thyroid uptake on FDG-PET, we believe that, if the patient's clinical status permits, the evaluation of patients with incidental thyroid PEToma should include ultrasonographic confirmation and fine-needle aspiration cytology.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".