Pancreatic Ductal Adenocarcinoma: Update of CT-Based Radiomics Applications in the Pre-Surgical Prediction of the Risk of Post-Operative Fistula, Resectability Status and Prognosis.

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Giulia Pacella, Maria Chiara Brunese, Eleonora D'Imperio, Marco Rotondo, Andrea Scacchi, Mattia Carbone, Germano Guerra

Author Information

Giulia Pacella: Department of Medicine and Health Science "V. Tiberio", University of Molise, 86100 Campobasso, Italy.
Maria Chiara Brunese: Department of Medicine and Health Science "V. Tiberio", University of Molise, 86100 Campobasso, Italy.
Eleonora D'Imperio: Radiology Unit, "A. Cardarelli" Hospital, 80131 Campobasso, Italy.
Marco Rotondo: Department of Medicine and Health Science "V. Tiberio", University of Molise, 86100 Campobasso, Italy.
Andrea Scacchi: General Surgery Unit, University of Milano-Bicocca, 20126 Milan, Italy. ORCID
Mattia Carbone: San Giovanni di Dio e Ruggi d'Aragona Hospital, 84131 Salerno, Italy.
Germano Guerra: Department of Medicine and Health Science "V. Tiberio", University of Molise, 86100 Campobasso, Italy. ORCID

PMID: 38068432 DOI: 10.3390/jcm12237380

BACKGROUND: Pancreatic ductal adenocarcinoma (PDAC) is the seventh leading cause of cancer-related deaths worldwide. Surgical resection is the main driver to improving survival in resectable tumors, while neoadjuvant treatment based on chemotherapy (and radiotherapy) is the best option-treatment for a non-primally resectable disease. CT-based imaging has a central role in detecting, staging, and managing PDAC. As several authors have proposed radiomics for risk stratification in patients undergoing surgery for PADC, in this narrative review, we have explored the actual fields of interest of radiomics tools in PDAC built on pre-surgical imaging and clinical variables, to obtain more objective and reliable predictors.
METHODS: The PubMed database was searched for papers published in the English language no earlier than January 2018.
RESULTS: We found 301 studies, and 11 satisfied our research criteria. Of those included, four were on resectability status prediction, three on preoperative pancreatic fistula (POPF) prediction, and four on survival prediction. Most of the studies were retrospective.
CONCLUSIONS: It is possible to conclude that many performing models have been developed to get predictive information in pre-surgical evaluation. However, all the studies were retrospective, lacking further external validation in prospective and multicentric cohorts. Furthermore, the radiomics models and the expression of results should be standardized and automatized to be applicable in clinical practice.

POPF artificial intelligence pancreatic ductal adenocarcinoma presurgical evaluation prognosis radiomic

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