PET/CT imaging of differentiated and medullary thyroid carcinoma using the novel SSTR-targeting peptide [18F]SiTATE – first clinical experiences
Bibliographic record
Abstract
Abstract Purpose The novel 18 F-labeled somatostatin receptor (SSTR)-directed radiotracer [ 18 F]SiTATE demonstrated promising results for the imaging of various SSTR-expressing tumor types. Although thyroid carcinomas (TC) express SSTR, data on [ 18 F]SiTATE PET/CT imaging in TC are lacking. This study explores the use of [ 18 F]SiTATE PET/CT in a patient cohort with histologically proven TC. Methods As part of a prospective observational study at a single tertiary cancer center, 21 patients with TC (10 medullary (MTC) and 11 differentiated (DTC)) who underwent at least one [ 18 F]SiTATE PET/CT were included (37 scans in total). Mean SUV max and SUV mean of tumoral lesions, mean total-tumor-volume (TTV), and whole-body (WB)-SUV max and WB-SUV mean on PET with their standard deviations (SDs) were determined. PET parameters were correlated to clinical parameters including tumor marker levels (thyroglobulin for DTC, calcitonin for MTC). Results 89 lesions were included in the analysis. Metastases were localized in the bone, lymph nodes, lung, soft tissue, and thyroid bed. Osseous (31 lesions; SUV max 8.6 ± 8.0; SUV mean 5.8 ± 5.4) and nodal (37 lesions; SUV max 8.7 ± 7.8; SUV mean 5.7 ± 5.4) metastases showed the highest uptake. The MTC disease burden on PET significantly correlated with the calcitonin tumor marker level (e.g., TTV: r = 0.771, r 2 = 0.594, p = 0.002). For DTC, no such correlation was present. Conclusion Our data demonstrate high feasibility of [ 18 F]SiTATE PET/CT in a small cohort of patients with MTC and DTC. The use of [ 18 F]SiTATE may overcome logistical disadvantages of 68 Ga-based tracers and facilitate SSTR-targeted PET/CT imaging of thyroid carcinoma.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.000 | 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".