Thyroid-Stimulating Hormone–Stimulated Fused Positron Emission Tomography/Computed Tomography in the Evaluation of Recurrence in <sup>131</sup> I-Negative Papillary Thyroid Carcinoma
Bibliographic record
Abstract
UNLABELLED: Fluorine-18 2-fluoro-2-deoxy-D-glucose positron emission tomography (FDG-PET) detects recurrence of papillary thyroid carcinoma (PTC) in thyroidectomized patients with elevated thyroglobulin (Tg) levels and negative (131)I-whole-body scans. This paper describes the utility of thyroid-stimulating hormone (TSH)-stimulated fused FDG-PET/computed tomography (CT) scanning on our first 15 patients of this population. METHODS: Patients were prepared for PET/CT imaging with thyroid hormone withdrawal (n = 7) or recombinant human TSH (n = 8). All other imaging before the PET/CT did not demonstrate evidence of recurrence. RESULTS: PET/CT scans revealed active foci in 9 patients, 4 prepared with hypothyroidism, and 5 with exogenous TSH. Positive results were demonstrated even in those with relatively low stimulated-TSH Tg values (13 and 14 microg/L). Six patients with positive PET/CT scans were treated surgically, yielding malignant tissue for 5 of those patients. CONCLUSION: PET/CT scans performed under TSH stimulation are an effective method of detecting of recurrence of PTC and direct surgical interventions, even in those with persistently elevated but relatively low Tg levels.
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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 | 0.002 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".