In this dataset

This collection provides public access to a 3D pathology dataset of prostate cancer, allowing researchers to further investigate various 3D tissue structures and their correlation with prostate cancer patient outcomes (biochemical recurrence).   These 3D tissue structures are revealed through: (1) a H&E-analog stain, (2) synthetically generated immunofluorescence staining of CK8 (targeting the luminal epithelial cells of all prostate glands), and (3) 3D segmentation masks of the gland lumen, epithelium, and stromal regions of prostate biopsies.  This data collection will promote research in the field of computational 3D pathology for clinical decision support.

In this TCIA collection, we provide the raw 3D open-top light-sheet (OTLS) microscope images of prostate biopsies stained with a fluorescent analog of H&E at original resolution (unfused image tiles), the 2x down-sampled fused OTLS-imaged images (H&E-analog

staining), the synthetic cytokeratin-8 (CK8) immunofluorescent images at 2x-downsampled resolution, the 3D

semantic segmentation masks of glands at 4x down-sampled resolution,

the clinical data for patient outcomes (biochemical recurrence), and the coordinates for the cancer

-enriched regions of each biopsy. All datasets are from the 50 patient cases

studied in

this publication: [W. Xie et al., Cancer Research, 2022].

This dataset will provide public access to a 3D pathology dataset of prostate cancer, allowing researchers to investigate further on various 3D tissue structures revealed by the H&E analog images of prostate biopsies, and their correlation with prostate cancer disease progression and patient outcome. This will promote more research in the field of computational 3D pathology for clinical decision support.

Additional Information: "The 3D pathology imaging data was generated in our lab with a custom light-sheet microscope, with Note that the 3D pathology datasets provided in this collection were generated in Dr. Jonathan Liu’s lab at the University of Washington with a custom open-top light-sheet (OTLS) microscope developed by the lab [A.K. Glaser et al., Nature Communications, 2019].  There is no clinical metadata within the imaging files and all patients are referred to with coded identifiers.  All of the clinical outcomes data that we will provide provided in this collection have already been published in tables within the supplement of our Cancer Research paper.  All cases are referred to based on a coded identifier only, so there should be no issues with de-identification."[W. Xie et al., Cancer Research, 2022].