18F-FDG PET/CT metabolic parameters predict prognosis in pancreatic ductal adenocarcinoma after neoadjuvant chemotherapy
Zhang, L.; Jin, L.
Show abstract
This study aimed to evaluate the prognostic value of quantitative analysis of {superscript 1}F-FDG positron emission tomography (PET)/computed tomography (CT) metabolic parameters in patients with pancreatic ductal adenocarcinoma (PDAC) after neoadjuvant chemotherapy (NACT). A retrospective analysis was conducted on the clinical and imaging data of 44 patients with pathologically confirmed PDAC who received NACT. All patients completed standard chemotherapy regimens and underwent {superscript 1}F-FDG PET/CT examinations within 2 weeks before and after chemotherapy. Multiple metabolic parameters of lesions were extracted, their percentage changes were calculated, and the optimal cut-off values for each parameter were determined. Kaplan-Meier survival analysis and Cox proportional hazards regression analysis were applied to explore the prognostic value of the metabolic parameters, and the prognostic stratification performance of PET Response Criteria in Solid Tumors (PERCIST) 1.0 was compared with that of Response Evaluation Criteria in Solid Tumors (RECIST) 1.1. PERCIST 1.0 demonstrated significantly superior prognostic stratification compared with RECIST 1.1. A peak standardized uptake value corrected for lean body mass (SULpeak2) > 3.07 and a percentage change in SULpeak between pre- and post-treatment scans ({Delta}SULpeak%) [≤] 37.66% were identified as independent risk factors for poor prognosis. Furthermore, SUL-related parameters exhibited markedly better predictive efficacy than traditional metabolic parameters such as the standardized uptake value and metabolic tumor volume. Quantitative analysis of {superscript 1}F-FDG PET/CT metabolic parameters can effectively predict prognosis in PDAC after NACT, and PERCIST 1.0 is a more optimal criterion for efficacy and prognostic assessment. A post-NACT SULpeak > 3.07 and {Delta}SULpeak% [≤] 37.66% were core independent indicators for predicting poor prognosis in these patients.
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