Dual Somatostatin Receptor/<sup>18</sup>F-FDG PET/CT Imaging in Patients with Well-Differentiated, Grade 2 and 3 Gastroenteropancreatic Neuroendocrine Tumors
Bibliographic record
Abstract
Our purpose was to prospectively assess the distribution of NETPET scores in well-differentiated (WD) grade 2 and 3 gastroenteropancreatic (GEP) neuroendocrine tumors (NETs) and to determine the impact of the NETPET score on clinical management. <b>Methods:</b> This single-arm, institutional ethics review board–approved prospective study included 40 patients with histologically proven WD GEP NETs. <sup>68</sup>Ga-DOTATATE PET and <sup>18</sup>F-FDG PET were performed within 21 d of each other. NETPET scores were evaluated qualitatively by 2 reviewers, with up to 10 marker lesions selected for each patient. The quantitative parameters that were evaluated included marker lesion SUV<sub>max</sub> for each tracer; <sup>18</sup>F-FDG/<sup>68</sup>Ga-DOTATATE SUV<sub>max</sub> ratios; functional tumor volume (FTV) and metabolic tumor volume (MTV) on <sup>68</sup>Ga-DOTATATE and <sup>18</sup>F-FDG PET, respectively; and FTV/MTV ratios. The treatment plan before and after <sup>18</sup>F-FDG PET was recorded. <b>Results:</b> There were 22 men and 18 women (mean age, 60.8 y) with grade 2 (<i>n</i> = 24) or grade 3 (<i>n</i> = 16) tumors and a mean Ki-67 index of 16.1%. NETPET scores of P0, P1, P2A, P2B, P3B, P4B, and P5 were documented in 2 (5%), 5 (12.5%), 5 (12.5%) 20 (50%), 2 (5%), 4 (10%), and 2 (5%) patients, respectively. No association was found between the SUV<sub>max</sub> of target lesions on <sup>68</sup>Ga-DOTATATE and the SUV<sub>max</sub> of target lesions on <sup>18</sup>F-FDG PET (<i>P</i> = 0.505). <sup>18</sup>F-FDG/<sup>68</sup>Ga-DOTATATE SUV<sub>max</sub> ratios were significantly lower for patients with low (P1–P2) primary NETPET scores than for those with high (P3–P5) primary NETPET scores (mean ± SD, 0.20 ± 0.13 and 1.68 ± 1.44, respectively; <i>P</i> < 0.001). MTV on <sup>18</sup>F-FDG PET was significantly lower for low primary NETPET scores than for high ones (mean ± SD, 464 ± 601 cm<sup>3</sup> and 66 ± 114 cm<sup>3</sup>, respectively; <i>P</i> = 0.005). A change in the type of management was observed in 42.5% of patients after <sup>18</sup>F-FDG PET, with the most common being a change from systemic therapy to peptide receptor radionuclide therapy and from debulking surgery to systemic therapy. <b>Conclusion:</b> There was a heterogeneous distribution of NETPET scores in patients with WD grade 2 and 3 GEP NETs, with more than 1 in 5 patients having a high NETPET score and a frequent change in management after <sup>18</sup>F-FDG PET. Quantitative parameters including <sup>18</sup>F-FDG/<sup>68</sup>Ga-DOTATATE SUV<sub>max</sub> ratios in target lesions and FTV/MTV ratios can discriminate between patients with high and low NETPET scores.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| 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 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".