Evidence map›Paper›PMID 42231766›Full record

ArticleNuclear medicine communications2026

Grading and detecting gastroenteropancreatic neuroendocrine neoplasms with dual-tracer ( 18 F-AlF-NOTA-octreotide/ 18 F-FDG) PET/CT: a metabolic parameter-based study.

Qing Dong, Qiuchen Zhou, Yang Liu, Qian Wang, Zhao Yang, Qian Su

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Article in Nuclear medicine communications, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Qing DongDepartment of Molecular Imaging and Nuclear Medicine, Tianjin Medical University Cancer Institute & Hospital; Tianjin Medical University Cancer Institute & Hospital, National Clinical Research Center for Cancer; Tianjin's Clinical Research Center for Cancer; Tianjin Key Laboratory of Digestive Cancer; Key Laboratory of Cancer Prevention and Therapy, Tianjin, China.
Qiuchen Zhou
Yang Liu
Qian Wang
Zhao Yang
Qian Su

Funding

Tianjin Key Medical Discipline Construction Project TJYXZDXK-3-004B
6 · The paper itself

Abstract

objectiveTo evaluate quantitative metabolic indices from dual-tracer 18 F-AlF-NOTA-octreotide ( 18 F-AlF-OC) and 18 F-fluorodeoxyglucose (FDG) PET/computed tomography (CT) for grading gastroenteropancreatic neuroendocrine neoplasms (GEP-NENs), focusing on total lesion glycolysis ratio (TLGR).

methodsThis retrospective study included 34 patients with GEP-NENs (198 target lesions) who underwent both 18 F-AlF-OC and 18 F-FDG PET/CT. Parameters included maximum standardized uptake value (SUV max ), total lesion glycolysis (TLG), SUV ratio (SUVR), and TLGR (ratio of 18 F-AlF-OC volumetric somatostatin receptor uptake to 18 F-FDG TLG by conventional TLG framework). Diagnostic performance for differentiating G1/G2 from G3/neuroendocrine carcinoma (NEC) and neuroendocrine tumor (NET) from NEC was assessed using receiver operating characteristic (ROC) analysis. Incremental value was evaluated using Δarea under the curve (AUC) and continuous net reclassification improvement with patient-level cluster bootstrap resampling. Generalized estimating equation (GEE) models accounted for multiple lesions per patient. Internal validation used leave-one-patient-out cross-validation.

results18 F-AlF-OC detected more lesions in G1/G2 NETs, while detection was similar in NEC. In ROC analysis, TLGR, SUVR, and TLGR + SUVR yielded AUCs of 0.760, 0.760, and 0.767 for G1/G2 versus G3/NEC, and 0.811, 0.829, and 0.827 for NET versus NEC, respectively. Adding TLGR to SUVR or FDG SUV max provided only modest improvement. TLGR was significant alone in GEE models but attenuated after SUVR adjustment, and cross-validation showed reduced out-of-sample performance.

conclusionDual-tracer PET/CT provides complementary information for GEP-NEN grading. TLGR is an exploratory volumetric dual-tracer parameter, but its incremental value beyond SUVR and FDG SUV max is limited. Further validation is required.

Indexed as

Fluorodeoxyglucose F18Heterocyclic CompoundsIntestinal NeoplasmsNeuroendocrine TumorsOctreotidePancreatic NeoplasmsPositron Emission Tomography Computed TomographyStomach NeoplasmsAdultAgedFemaleHeterocyclic Compounds, 1-RingHumansMaleMiddle AgedNeoplasm Grading1,4,7-triazacyclononane-N,N',N''-triacetic acidFluorodeoxyglucose F18Heterocyclic CompoundsHeterocyclic Compounds, 1-RingOctreotidegastroenteropancreatic neuroendocrine neoplasmsPETstandardized uptake value ratiototal lesion glycolysis ratio

Identifiers

PMID42231766
PMCPMC13552563

What Socratic holds

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.