{Reference Type}: Journal Article {Title}: 18F-FDG PET/CT metabolism multi-parameter prediction of chemotherapy efficacy in locally progressive gastric cancer. {Author}: Jin L;Zhang L;Fu L;Song F;Cheng A; {Journal}: Ann Nucl Med {Volume}: 38 {Issue}: 6 {Year}: 2024 Jun 27 {Factor}: 2.258 {DOI}: 10.1007/s12149-024-01921-9 {Abstract}: OBJECTIVE: 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.
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.