biostudies-literatureBhasker NDeutsches Krebsforschungszentrum (DKFZ)German Federal Ministry of Health7506https://www.ebi.ac.uk/biostudies/studies/S-EPMC10169866biostudies-literatureUnknown13(1)Clinically relevant postoperative pancreatic fistula (CR-POPF) can significantly affect the treatment course and outcome in pancreatic cancer patients. Preoperative prediction of CR-POPF can aid the surgical decision-making process and lead to better perioperative management of patients. In this retrospective study of 108 pancreatic head resection patients, we present risk models for the prediction of CR-POPF that use combinations of preoperative computed tomography (CT)-based radiomic features, mesh-based volumes of annotated intra- and peripancreatic structures and preoperative clinical data. The risk signatures were evaluated and analysed in detail by visualising feature expression maps and by comparing significant features to the established CR-POPF risk measures. Out of the risk modelScientific reportsPrediction of clinically relevant postoperative pancreatic fistula using radiomic features and preoperative data.PMC101698662520DAT82Leger SKuhn JPBhasker NHoffmann RTSkorobohach NKolbinger FRLock SDistler MSpeidel SWeitz JZwanenburg AfalsePrediction of clinically relevant postoperative pancreatic fistula using radiomic features and preoperative data.Clinically relevant postoperative pancreatic fistula (CR-POPF) can significantly affect the treatment course and outcome in pancreatic cancer patients. Preoperative prediction of CR-POPF can aid the surgical decision-making process and lead to better perioperative management of patients. In this retrospective study of 108 pancreatic head resection patients, we present risk models for the prediction of CR-POPF that use combinations of preoperative computed tomography (CT)-based radiomic features, mesh-based volumes of annotated intra- and peripancreatic structures and preoperative clinical data. The risk signatures were evaluated and analysed in detail by visualising feature expression maps and by comparing significant features to the established CR-POPF risk measures. Out of the risk model2023-01-01T00:00:00Z2023 May2026-06-03T19:55:18.658Z2025-04-06T01:05:54.504ZS-EPMC101698663716100710.1038/s41598-023-34168-x