18F-PET/CT imaging of metastasis to the thyroid gland: Imaging findings and effect on patient management
Bibliographic record
Abstract
Purpose: While metastasis to the thyroid from a primary cancer remote to the thyroid is uncommon, current imaging techniqueshave improved detection of these intrathyroid metastases. The purpose of this study was to evaluate the 18F-PET/CT appearanceof intrathyroid metastases and assess the impact of detection on patient management.Methods: The 18F-PET/CT appearance of intrathyroid metastasis, including standardized uptake value (SUV), disease extent,and the effect on patient management following diagnosis were retrospectively reviewed. Inclusion criteria included 18F-PET/CTimaging and diagnosis of the intrathyroid metastasis matching the remote primary tumor.Results: Intrathyroid metastasis were detected in 24 patients. The intrathyroid metastases presented on 18F-PET/CT as focalnodular uptake (n = 21), multiple nodular uptake (n = 2), or diffuse uptake/infiltration of the thyroid gland (n = 1). The SUVranged between 3.9 and 42 (median 12.5 ± 7.5); in 2 patients, the FDG-avidity was minimal. On 18F-PET/CT, distant metastaseswere present outside the neck (n = 18), or limited to the neck (n = 6). In 2 of these 6 patients, the thyroid was the only site ofmetastatic disease. Due to the metastatic disease, the therapy was changed in 23 of 24 patients; 1 patient was lost to follow-up.Conclusion: In any patient with a previous or current history of an extrathyroid malignancy, an 18FDG-avid thyroid mass ordiffuse infiltration of the thyroid on 18F-PET/CT should be considered a potential intrathyoid metastasis until proven otherwise.Knowledge of an intrathyroid metastasis may impact patient management, especially if the thyroid or neck are the only sites ofmetastatic disease.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".