3D pathology of prostate biopsies with biochemical recurrence outcomes: raw H&E-analog datasets and image translation-assisted segmentation in 3D (ITAS3D) datasets (PCa_Bx_3Dpathology)

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].
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 provided in this collection have already been published within the supplement of [W. Xie et al., Cancer Research, 2022].

本数据集开放前列腺癌三维病理数据集的公共访问权限，以供研究人员深入探究各类三维组织结构及其与前列腺癌患者预后（生化复发）的关联。上述三维组织结构可通过以下三种方式可视化呈现：(1) 类苏木精-伊红（H&E-analog）染色；(2) 人工合成的细胞角蛋白8（CK8）免疫荧光染色（靶向所有前列腺腺体的腔面上皮细胞）；(3) 前列腺活检组织中腺体管腔、上皮及间质区域的三维语义分割掩码。本数据集将推动面向临床决策支持的计算三维病理领域研究发展。

在本癌症图像档案（The Cancer Imaging Archive, TCIA）数据集集中，我们提供以下多类数据：原始分辨率下、经类H&E荧光染色的前列腺活检组织三维开源顶光片显微镜（open-top light-sheet, OTLS）原始图像（未融合图像块）、2倍下采样的融合式OTLS成像图像（对应类H&E染色结果）、2倍下采样分辨率的合成细胞角蛋白8（CK8）免疫荧光图像、4倍下采样分辨率的腺体三维语义分割掩码、前列腺癌患者临床预后数据（生化复发情况），以及每例活检组织的癌富集区域坐标。所有数据集均来自本研究[W. Xie等，《癌症研究》，2022]中纳入的50例患者病例。

需说明的是，本数据集集中的三维病理数据集由华盛顿大学乔纳森·刘（Jonathan Liu）博士实验室利用该实验室自主研发的定制化开源顶光片显微镜（OTLS）生成[A.K. Glaser等，《自然·通讯》，2019]。成像文件中不包含临床元数据，所有患者均以编码标识符进行匿名处理。本数据集提供的所有临床预后数据均已发表于[W. Xie等，《癌症研究》，2022]的补充材料中。

搜集汇总

背景与挑战

背景概述

该数据集是一个前列腺癌3D病理学公开数据集，包含50个患者病例的原始3D显微镜图像、合成免疫荧光图像、3D语义分割掩码和生化复发临床数据，旨在支持计算3D病理学研究以关联组织结构与患者预后。数据集通过H&E-analog染色和图像翻译辅助分割技术揭示三维组织特征，促进临床决策支持领域的发展。