Comparison of somatostatin receptor expression in patients with neuroendocrine tumours with and without somatostatin analogue treatment imaged with [18F]SiTATE
Bibliographic record
Abstract
Ziel/Aim Somatostatin analogues (SSA) are frequently used in the treatment of neuroendocrine tumours. With 18 F-SiTATE recently entering the field of somatostatin receptor (SSTR) positron emission tomography (PET)/ computed tomography (CT) imaging, the purpose of this study was to compare the SSTR-expression of differentiated gastroentero-pancreatic neuroendocrine tumours (GEP-NET) measured by 18 F-SiTATE-PET/CT in patients with and without previous treatment with long-acting SSAs to evaluate if SSA treatment needs to be paused prior to 18 F-SiTATE-PET/CT. Methodik/Methods 76 patients were examined with standardized 18 F-SiTATE-PET/CT within clinical routine: 39 patients received long-acting SSA up to 21 days prior to PET/CT examination and 37 patients without pre-treatment with SSAs. Maximum and mean standardized uptake values (SUV max and SUV mean ) of tumours and metastases (liver, lymphnode, mesenteric/peritoneal and bones) as well as representative background tissues (liver, spleen, adrenal gland, blood pool, small intestine, lung, bone) were measured, standard uptake value ratios (SUVR) between tumours/metastases and liver, likewise between tumours/metastases and corresponding specific background were calculated and compared between the two groups. Ergebnisse/Results SUV mean of liver (5.36±1.51 vs. 6.77±1.85) and spleen (17.40±6.85 vs. 36.69±10.30) were significantly lower (p<0.001) and SUV mean of blood pool (1.69±0.56 vs. 1.27±0.35) was significantly higher (p<0.001) in patients with SSA pre-treatment compared to patients without. No significant differences between tumour-to-liver and specific tumour-to-background SUVRs were observed between both groups (all p>0.05). Schlussfolgerungen/Conclusions In patients previously treated with SSAs, a significantly lower SSTR expression ( 18 F-SiTATE uptake) in normal liver and spleen tissue was observed, as previously reported for 68 Ga-labelled SSAs, without significant reduction of tumour-to-background contrast. Therefore, there is no evidence that SSA treatment needs to be paused prior to 18 F-SiTATE-PET/CT. Publication History Article published online: 14 April 2022 © 2022. Thieme. All rights reserved. Georg Thieme Verlag KG Rüdigerstraße 14, 70469 Stuttgart, Germany
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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 | 0.001 |
| 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 | 0.000 |
| 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".