{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"submitter":["Bhasker N"],"funding":["Deutsches Krebsforschungszentrum (DKFZ)","German Federal Ministry of Health"],"pagination":["7506"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC10169866"],"repository":["biostudies-literature"],"omics_type":["Unknown"],"volume":["13(1)"],"pubmed_abstract":["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 model"],"journal":["Scientific reports"],"pubmed_title":["Prediction of clinically relevant postoperative pancreatic fistula using radiomic features and preoperative data."],"pmcid":["PMC10169866"],"funding_grant_id":["2520DAT82"],"pubmed_authors":["Leger S","Kuhn JP","Bhasker N","Hoffmann RT","Skorobohach N","Kolbinger FR","Lock S","Distler M","Speidel S","Weitz J","Zwanenburg A"],"additional_accession":[]},"is_claimable":false,"name":"Prediction of clinically relevant postoperative pancreatic fistula using radiomic features and preoperative data.","description":"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 model","dates":{"release":"2023-01-01T00:00:00Z","publication":"2023 May","modification":"2026-06-03T19:55:18.658Z","creation":"2025-04-06T01:05:54.504Z"},"accession":"S-EPMC10169866","cross_references":{"pubmed":["37161007"],"doi":["10.1038/s41598-023-34168-x"]}}