18F-FDG PET/CT metabolism multi-parameter prediction of chemotherapy efficacy in locally progressive gastric cancer

Author:

jin luqiang1,zhang linghe1,fu liping1,song fahuan1,Cheng aiping1ORCID

Affiliation:

1. Zhejiang Provincial People's Hospital

Abstract

Abstract Purpose: This study aimed to use an 18F-FDG PET/CT multiparametric quantitative analysis to determine the efficacy of neoadjuvant chemotherapy in patients with locally progressive gastric cancer. Materials and Methods: We conducted a retrospective analysis of 34 patients with pathologically identified gastric cancer who received neoadjuvant chemotherapy and surgery. Chemotherapy regimens were followed and 18F-FDG PET/CT was conducted. We ascertained multiparamaters of the target lesions pre- and post-treatment and determined the ideal cutoff values for the percentage change in biomarkers. Independent factors were evaluated using binary logistic regression. A response classification system was used to explore the association between metabolic and anatomical responses and the degree of pathological remission. Results: Binary logistic regression analysis showed that Lauren bowel type and change in total lesion glycolysis >45.2% were risk predictors for the efficacy of neoadjuvant chemotherapy; total lesion glycolysis demonstrated the best predictive efficacy. The categorical variable system of the two-module response (metabolic and anatomical response) group had a higher predictive accuracy than that of the single-module response (metabolic or anatomical response) group. Conclusions: Using 18F-FDG PET/CT multiparametric quantitative analysis, Lauren bowel type and change in total lesion glycolysis >45.2% were independent predictors of the efficacy of neoadjuvant chemotherapy in patients with gastric adenocarcinoma. Additionally, the dual-module assessment demonstrated high predictive efficacy. Trial Registration Number:MR-33-23-034719 2023.09.07 Review the registration

Publisher

Research Square Platform LLC

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