Prediction of Surgical Resectability After FOLFIRINOX Chemotherapy for Borderline Resectable and Locally Advanced Pancreatic Cancer: the Role of Diffusion Weighted Magnetic Resonance Imaging, Radiomics and Liquid Biopsy

In this prospective study, new diagnostic tools will be explored for patients with borderline resectable and locally advanced pancreatic ductal adenocarcinoma (BR or LAPDA) who undergo neoadjuvant chemotherapy with FOLFIRINOX. The diagnostic work-up and therapy for the study population will not differ from the gold standard during the study; only additional diagnostic tools will be implemented, and their value will be analyzed post hoc.

The 5-year survival rate of pancreatic cancer is 9%, but this can be drastically improved if surgery is possible. With its increasing incidence and poor prognosis, pancreatic cancer is becoming a global oncologic challenge where major breakthroughs are still required to improve patient outcomes. Patients with BR or LAPDA typically undergo neoadjuvant treatment with FOLFIRINOX chemotherapy, followed by referral for surgery if a response is observed. In these cases, surgical resectability is difficult to predict based on CT imaging due to the tumor's desmoplastic reaction, which obscures tumor-vessel contact without clear morphological changes. Consequently, patients without tumor progression on CT and with a decreased tumor marker (CA 19-9) are considered for surgical exploration to ensure that no potentially curative treatment is denied. However, the non-specific nature of CA 19-9 and the unreliable spatial changes on CT do not allow for accurate patient stratification. Therefore, alternative diagnostic strategies are needed to better predict resectability, minimizing unnecessary laparotomies while ensuring that potentially curative approaches are not overlooked.

In this project, the investigator will apply diffusion-weighted magnetic resonance imaging (DW-MRI), as it has been shown to be useful in assessing tumor response beyond morphological parameters. DW-MRI enables the detection of functional tumor changes, variations in vascularization, and fibrosis without modifications in shape. The statistical evaluation of visual information using radiomics optimizes data analysis, allowing comparisons over time (before and after chemotherapy) and correlation with operative findings (resectable or unresectable tumor).

The investigator will focus on patients with BR and LAPDA and assess whether a combination of clinical and genetic factors can predict successful surgical resection. To this end, DW-MRI imaging will be complemented by multi-omics profiling in liquid biopsies. Furthermore, the investigator aims to validate, in a prospective patient cohort, the predictive value of recently published single nucleotide polymorphisms (SNPs) in genes that regulate cancer progression, invasion, and metastasis. Some alleles of these SNPs have been associated with an increased risk of tumor-related mortality compared to protective genotypes.