Computational pathology software for integrative cancer research with three-dimensional digital slides

项目总结： 基于组织的研究仍然是癌症研究的基石。随着具有成本效益的数字技术的出现 扫描仪，大规模的定量研究现在是可行的，使用高通量分析两个- 维度(2D)图像数据集。然而，2D图像分析有其局限性，因为病理疾病 发生在三维(3D)空间中，并且2D表示遭受显著的信息损失。那里 是3D分析性数字病理学的主要差距，包括缺乏图像分析工具来定量 处理3D数据量，缺乏有效且可扩展的数据管理和分析基础架构 对大规模空间病理特征和生物标志物进行建模、整理、查询和挖掘。我们建议填补 这些差距与新的信息学解决方案旨在更好地理解3D肿瘤微环境， 胰腺导管免疫增强型免疫细胞浸润的免疫治疗研究 脑肿瘤胶质母细胞瘤的腺癌与肿瘤快速发展的病理生理学研究 (GBM)。根据人类肿瘤图谱计划，我们建议创建一个新颖而全面的3D数字 用于定量分析病理特征和空间模式的病理分析框架 具有定量数字的真实3D组织环境中与疾病进展相关的生物标记物 病理图像体处理、空间一体化组织学-分子图像分析、大尺度 空间数据分析和关键细胞间隔跟踪，用于临床治疗反应测试和 免疫治疗的发展。使信息学工具能够广泛用于3D数字病理成像数据 在癌症研究方面，我们将进一步升级一个全面的、基于网络的多模式显微镜系统 图像管理、传播和可视化。我们将利用大量的信息学工具和 我们开发的算法用于显微图像分析，综合转化型癌症研究， 病理空间分析，以及过去14年的高性能计算。开发的工具将是 由一系列资金雄厚的癌症研究项目测试和使用，这些项目涉及胰腺癌、脑瘤、头部 以及颈部、肝癌和肺癌。拟议的信息学工具将使精确和全面 关键过渡阶段的组织学、分子、细胞和组织水平相互作用的特征 癌症进展。他们还将允许精确询问物理和空间特征 免疫细胞对肿瘤的侵袭及宿主免疫系统与肿瘤细胞的相互作用 在复杂的肿瘤微环境中转移，对于免疫治疗的发展至关重要。 拟议研究的完成将会提升我们大规模的资讯科技能力。 显微图像分析，帮助癌症研究人员准确了解癌症生物学和进展 机制，并使临床医生能够轻松地从大规模获取临床相关信息 用于计算机诊断和治疗发展的显微图像。

PROJECT SUMMARY: Tissue-based investigation remains a cornerstone of cancer research. With the advent of cost-effective digital scanners, large-scale quantitative investigations are now feasible using high throughput analysis of two- dimensional (2D) image datasets. However, 2D image analytics has its limitations, since pathologic diseases occur in three-dimensional (3D) space and 2D representations suffer from significant information loss. There are major gaps for 3D analytical digital pathology, including lack of image analysis tools to quantitatively process 3D data volumes and lack of an effective and scalable data management and analytical infrastructure to model, curate, query and mine large-scale spatial pathology features and biomarkers. We propose to fill these gaps with a new informatics solution directed at better understanding of 3D tumor micro-environments, with driving use cases on immunotherapy study for enhanced immune cell infiltration for pancreatic ductal adenocarcinoma (PDAC) and pathophysiological study of rapid tumor progression in brain tumor glioblastoma (GBM). In line with Human Tumor Atlas program, we propose to create a novel and comprehensive 3D digital pathology analytics framework to quantitatively analyze spatial patterns of pathologic hallmarks and biomarkers related to disease progression in an authentic 3D tissue environment with quantitative digital pathology image volume processing, spatially integrative histology-molecular image analysis, large-scale spatial data analytics, and key cellular compartment tracking for clinical treatment response test and immunotherapy development. To enable a wide use of informatics tools for 3D digital pathology imaging data in cancer research, we will further upgrade a comprehensive, web-based system for multi-modality microscopy image management, dissemination, and visualization. We will leverage a large set of informatics tools and algorithms we have developed for microscopy image analysis, integrative translational cancer research, pathology spatial analytics, and high performance computing in the past 14 years. The developed tools will be tested and used by a suite of well-funded cancer research projects on pancreatic cancer, brain tumor, head and neck, liver, and lung cancers. The proposed informatics tools will enable precise and comprehensive characterizations of the histologic, molecular, cellular and tissue-level interactions at critical transition stages in cancer progression. They will also allow for a precise interrogation of physical and spatial signatures of immune cell infiltration into tumors, and the interactions between the host immune system and tumor cell metastasis within a complex tumor micro-environment architecture, essential for immunotherapy development. The completion of the proposed study will boost our informatics technology capabilities for large scale microscopy image analytics, help cancer researchers accurately understand cancer biology and progression mechanisms, and enable clinicians an easy access to clinically relevant information from large scale microscopy images for computer based diagnosis and therapeutic development.