Rationale and objectives: Clinically relevant postoperative pancreatic fistula (CR-POPF) is a threatening complication in body and/or tail pancreatic ductal adenocarcinoma (PDAC) receiving distal pancreatectomy (DP) and is difficult to predict preoperatively. We aimed to identify the role of baseline CT-based body composition analysis and extracellular volume (ECV) map in predicting the risk of CR-POPF preoperatively.
Materials and methods: A total of 329 resectable PDAC patients were enrolled and underwent multiphasic contrast-enhanced CT. Body composition indicators were calculated, and ECV maps were generated through multiphasic CT images. The differences in clinical variables and quantitative parameters between CR-POPF and non-CR-POPF patients were compared. Correlations between ECV fraction and pancreatic fibrosis stage were analyzed. Multivariate logistic regression was performed to screen the independent predictors and develop prediction models for CR-POPF. Receiver operating characteristic curve was utilized to evaluate the predictive performance.
Results: Among 329 patients, 19.76% (65/329) developed CR-POPF. Albumin, pancreatic texture, and intraoperative blood loss were used to build the clinical model with an AUC of 0.764. ECV fraction and total muscle ratio (TMR) were chosen to build the radiological model with an AUC of 0.872. A combined nomogram integrated with albumin, ECV fraction, and TMR could significantly improve the discrimination ability to an AUC of 0.924 (Delong test, all p < 0.05). The ECV fraction showed high positive correlation with histological fibrosis grade (Spearman ρ = 0.81).
Conclusion: CT-based body composition analysis and ECV exhibited great potential for predicting CR-POPF in body and/or tail PDAC after DP. The combined nomogram could further improve the predictive performance.
Keywords: Body composition; Extracellular space; Multidetector computed tomography; Pancreatectomy; Pancreatic fistula.
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