PDF(Pubmed)
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.
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.
摘要：
目的：本研究旨在使用18F-FDGPET/CT多参数定量分析来确定新辅助化疗对局部进展性胃癌患者的疗效。
方法：我们对34例经病理证实接受新辅助化疗和手术的胃癌患者进行了回顾性分析。遵循化疗方案并进行18F-FDGPET/CT。我们确定了治疗前后靶病变的多参数，并确定了生物标志物变化百分比的理想临界值。采用二元logistic回归对独立因素进行评价。反应分类系统用于探索代谢和解剖反应与病理缓解程度之间的关联。
结果：二元logistic回归分析显示，Lauren肠型和总病变糖酵解改变>45.2%是新辅助化疗疗效的风险预测因子；总病变糖酵解显示最佳预测效果。两模块反应（代谢和解剖反应）组的分类变量系统比单模块反应（代谢或解剖反应）组具有更高的预测准确性。
结论：使用18F-FDGPET/CT多参数定量分析，Lauren肠型和总病变糖酵解改变>45.2%是胃腺癌患者新辅助化疗疗效的独立预测因子。此外,双模块评估显示出较高的预测效能.
方法：我们对34例经病理证实接受新辅助化疗和手术的胃癌患者进行了回顾性分析。遵循化疗方案并进行18F-FDGPET/CT。我们确定了治疗前后靶病变的多参数，并确定了生物标志物变化百分比的理想临界值。采用二元logistic回归对独立因素进行评价。反应分类系统用于探索代谢和解剖反应与病理缓解程度之间的关联。
结果：二元logistic回归分析显示，Lauren肠型和总病变糖酵解改变>45.2%是新辅助化疗疗效的风险预测因子；总病变糖酵解显示最佳预测效果。两模块反应（代谢和解剖反应）组的分类变量系统比单模块反应（代谢或解剖反应）组具有更高的预测准确性。
结论：使用18F-FDGPET/CT多参数定量分析，Lauren肠型和总病变糖酵解改变>45.2%是胃腺癌患者新辅助化疗疗效的独立预测因子。此外,双模块评估显示出较高的预测效能.
