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Abstract Background The worldwide increase of pancreatic ductal adenocarcinoma (PDAC), which still has one of the lowest survival rates, requires novel imaging tools to improve early detection and to refine diagnosis. Therefore, the aim of this study was to assess the feasibility of propagation-based phase-contrast X-ray computed tomography of already paraffin-embedded and unlabeled human pancreatic tumor tissue to achieve a detailed three-dimensional (3D) view of the tumor sample in its entirety. Methods Punch biopsies of areas of particular interest were taken from paraffin blocks after initial histological analysis of hematoxylin and eosin stained tumor sections. To cover the entire 3.5 mm diameter of the punch biopsy, nine individual tomograms with overlapping regions were acquired in a synchrotron parallel beam configuration and stitched together after data reconstruction. Due to the intrinsic contrast based on electron density differences of tissue components and a voxel size of 1.3 μm achieved PDAC and its precursors were clearly identified. Results Characteristic tissue structures for PDAC and its precursors, such as dilated pancreatic ducts, altered ductal epithelium, diffuse immune cell infiltrations, increased occurrence of tumor stroma and perineural invasion were clearly identified. Certain structures of interest were visualized in three dimensions throughout the tissue punch. Pancreatic duct ectasia of different caliber and atypical shape as well as perineural infiltration could be contiguously traced by viewing serial tomographic slices and by applying semi-automatic segmentation. Histological validation of corresponding sections confirmed the former identified PDAC features. Conclusion In conclusion, virtual 3D histology via phase-contrast X-ray tomography visualizes diagnostically relevant tissue structures of PDAC in their entirety, preserving tissue integrity in label-free, paraffin embedded tissue biopsies. In the future, this will not only enable a more comprehensive diagnosis but also a possible identification of new 3D imaging tumor markers.