Intraductal Papillary Mucinous Neoplasms (IPMN) are recognized as important precursors to invasive pancreatic ductal adenocarcinoma (PDAC). While IPMN requires surveillance without treatment, a clinical marker is lacking which can identify those undergoing malignant transformation. In two genetic engineered mouse models (KPC and CKS), which resemble human PDAC and IPMN, respectively, we tested the hypothesis that differences in cellular architecture and stromal features between PDAC and IPMN present themselves in DW-MRI and /or DCE-MRI metrics. Our data revealed an almost complete separation of ADC values between CKS (benign) vs. KPC (malignant) tumors and identified histopathological features corroborating the imaging metrics.

Dynamic contrast enhanced MRI data in the abdomens of small animal models is often corrupted due to the effects respiratory and peristaltic motion. Here a DCE protocol that employs stack of stars sampling throughout was implemented and was shown to be robust with respect to motion artifacts. The sampling scheme also facilitates image reconstruction methods that employ view sharing, notably KWIC, yielding images with high temporal and spatial resolution. The protocol was demonstrated in an orthotopic murine model of pancreatic cancer. The resulting data were analyzed using the reference tissue method and provided high quality Ktrans and ve parameter maps.

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