Dual-tracer (18F-FDG and 18F-DOPA) PET/CT in evaluation of neuroendocrine tumors: An Asian study
Bibliographic record
Abstract
563 Objectives Neuroendocrine tumors (NETs) are rare malignancies originating from neural crest cells throughout the body. 18F-FDG PET/CT is known to have limited role in NET detection. Data of 18F-DOPA PET/CT on NET have been mostly reported by the Western countries. We aimed to evaluate the incremental value of dual-tracer (18F-FDG and 18F-DOPA) PET/CT to 18F-DOPA alone in the assessment of NET in Asian patients. Methods Patients with known or suspected NETs referred for PET/CT during year 2007~10 were retrospectively reviewed and those with histopathological confirmation before or after PET/CT within 2 months or with uneventful findings upon serial PET/CT within 6 months were recruited into this study. All patients underwent two-day protocol of 18F-FDG and 18F-DOPA PET/CT within 1 week. Pre-medication with Carbidopa (200 mg) was given orally 60 minutes before 18F-DOPA injection. Whole-body PET/CT was performed 60 minutes after tracer injection and PET/CT images were reviewed by 3 nuclear medicine physicians in consensus. Results 26 patients (M: 16, F: 10, mean age: 53±18.3 years) with/without treatment (untreated: 12, treated: 14) before PET/CT were evaluated. Histopathological results confirmed NETs in 23 patients with primary sites at adrenal gland (N=4), rectum (3), colon (2), stomach (1), pancreas (4), appendix (1), urinary bladder (1), thyroid (1), neck (1) and unknown primary with hepatic NET metastases (5). 18F-DOPA PET/CT was true positive in 16/23 and false negative (FN) in 7/23. Of the 7 FN patients, 18F-FDG PET/CT was able to detect 4/7: pancreas (2), rectum (1) and liver (1). Therefore the sensitivity of 18F-DOPA alone versus dual-tracer PET/CT was 70% (16/23) versus 87% (20/23), respectively. The remaining 3 FN patients all had very small colonic carcinoid lesions (2mm, 3mm and 6mm). For the 3 negative patients confirmed by serial PET/CT, both 18F-DOPA and 18F-FDG PET/CT showed true negative findings (specificity: 100%). Conclusions Dual-tracer PET/CT has an incremental value to 18F-DOPA alone in increasing the detection sensitivity for NET patients
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".