Background: Ga-labeled fibroblast activation protein inhibitor (FAPI) PET has emerged as a promising alternative, prompting multiple systematic reviews and meta-analyses with heterogeneous findings. Objective: We are aimed at synthesizing and appraise meta-analytic evidence on PET imaging in gastric cancer, with a focus on radiopharmaceutical-specific performance by clinical indication and certainty of evidence to inform personalized tracer selection. Methods: An umbrella review was conducted in accordance with PRISMA 2020. The protocol was prospectively registered in the Open Science Framework (OSF). PubMed, Scopus, and Web of Science were searched from inception to December 2025 for systematic reviews and meta-analyses evaluating PET imaging in gastric cancer. Outcomes included diagnostic accuracy, staging and restaging performance, recurrence detection, prognostic associations, methodological quality (AMSTAR-2), and certainty of evidence (GRADE). Results: Ga-FAPI PET generally showed higher pooled sensitivity than FDG for primary tumor detection, nodal disease, peritoneal metastases, and recurrence detection across available meta-analyses, although the certainty of evidence ranged from low to moderate and some findings were derived from mixed-population reviews. Conclusions: Available meta-analytic evidence suggests an indication-driven, personalized approach to PET imaging in gastric cancer. FDG PET remains useful for prognostic stratification and selected recurrence settings, whereas FAPI PET appears to offer higher diagnostic sensitivity for staging and restaging, particularly for peritoneal disease. Nevertheless, the overall certainty of evidence remains limited by heterogeneity, indirectness, and the absence of updated de novo pooled analyses.
Building similarity graph...
Analyzing shared references across papers
Loading...
Aiganym Amrenova
Alma Shukirbekova
Sholpan Akhelova
International Journal of Biomedical Imaging
National Nuclear Center of the Republic of Kazakhstan
Astana Medical University
Semey Medical University
Building similarity graph...
Analyzing shared references across papers
Loading...
Amrenova et al. (Thu,) studied this question.
www.synapsesocial.com/papers/69fada7f03f892aec9b1e446 — DOI: https://doi.org/10.1155/ijbi/3450212