Abstract
BACKGROUND: Predicting early recurrence (ER), (≤ 12 months) after pancreatic ductal adenocarcinoma (PDAC) resection remains challenging. Preoperative biomarkers such as carbohydrate antigen 19-9 (CA19-9) and computed tomography (CT) lack optimal specificity and reproducibility. Extracellular volume (ECV), measured on equilibrium-phase CT to quantify stromal fibrosis, correlates with PDAC progression but its utility for ER prediction is unknown. This study evaluates preoperative CT-ECV as a novel biomarker to predict ER following curative-intent PDAC resection. AIM: To investigate the utility of CT-ECV for preoperative prediction of ER in PDAC patients after R0 resection. METHODS: This retrospective study included 93 PDAC patients undergoing R0 resection and preoperative pancreatic CT from January 2020 to November 2023. Clinical and CT features were analyzed. ECV was calculated using unenhanced and equilibrium-phase CT. Univariable and multivariable Cox regression identified ER predictors, followed by receiver operating characteristic analysis. Recurrence-free survival (RFS) was assessed by the Kaplan-Meier method. RESULTS: Multivariable analysis identified elevated CT-ECV [hazard ratio (HR) = 1.05; 95% confidence interval (CI): 1.02-1.09; P = 0.003], high preoperative CA19-9 (HR = 1.00; 95%CI: 1.00-1.00; P = 0.002), and poor tumor grade (HR = 2.51; 95%CI: 1.20-5.22; P = 0.014) as independent ER predictors. CT-ECV demonstrated comparable predictive accuracy to tumor grade [areas under the curve (AUC): 0.736 vs 0.650; P = 0.202]. Combining CT-ECV and CA19-9 achieved a higher AUC than tumor grade alone (0.759 vs 0.650; P < 0.05). Kaplan-Meier analysis revealed significantly shorter RFS in patients with low CT-ECV (≤ 35.37%), elevated CA19-9 (> 55 U/mL), or poorly differentiated tumors compared to those with high CT-ECV (> 35.37%), low CA19-9 (≤ 55 U/mL), or moderately/well-differentiated tumors. CONCLUSION: CT-derived ECV is a promising non-invasive biomarker for preoperative ER prediction in PDAC. Combined with CA19-9, it outperforms tumor grade in stratifying recurrence risk, offering a clinically actionable tool for optimizing postoperative management.