Tools to Analyze Morphology and Spatially Mapped Molecular Data

项目描述（由申请人提供）：本项目旨在开发、部署和传播一套开源工具和集成信息学平台，为癌症研究提供高分辨率整片组织图像数据、空间映射遗传学和分子数据的多尺度、相关分析。该平台将在支持肿瘤发生、发展、异质性、侵袭和转移的研究中发挥重要作用。这些工具将允许对形态学和空间映射的遗传学和分子数据之间的相互作用进行定量分析，并将用于预测治疗结果和反应的研究、放射基因组学和定量放射学成像研究以及确定癌症靶点的研究。该软件和方法将使研究人员能够组装和可视化来自各种显微镜仪器的组织形态变化的详细，多尺度描述，并使其能够有效地管理，询问和探索多尺度的显微镜成像数据，并识别和分析个体和群体的特征。该项目将建立并扩展我们在过去15年中在显微镜成像、综合图像分析、高性能计算、数据库和可视化方面开发的软件和方法，并将利用、集成和调整哈佛切片机平台。信息学平台的设计和实施将由四项资金充足的前沿癌症研究以及许多额外的合作努力推动，包括癌症成像档案（TCIA）、梅奥诊所定量成像网络网站、结肠癌家族登记处和息肉预防研究。

DESCRIPTION (provided by applicant): This project is to develop, deploy, and disseminate a suite of open source tools and integrated informatics platform that will facilitate multi-scale, correlative analyses of high resolution whole slide tissue image data, spatially mapped genetics and molecular data for cancer research. This platform will play an essential role in supporting studies of tumor initiation, development, heterogeneity, invasion, and metastasis. These tools will allow quantitative analyses of the interplay between morphology and spatially mapped genetics and molecular data and will be used in studies that predict outcome and response to treatment, in radiogenomic and quantitative radiology imaging studies and in studies to identify cancer targets. The software and methods will enable researchers to assemble and visualize detailed, multi-scale descriptions of tissue morphologic changes originating from a wide range of microscopy instruments and make it possible to efficiently manage, interrogate, and explore microscopy imaging data at multiple scales and to identify and analyze features across individuals and cohorts. The project will build on and extend the software and methods we have developed in microscopy imaging, integrative image analysis, high performance computing, databases, and visualization over the past fifteen years and will also leverage, integrate and adapt the Harvard Slicer platform. The design and implementation of the informatics platform will be driven by four well funded, leading edge cancer focused studies along with many additional collaborative efforts including the Cancer Imaging Archive (TCIA), the Mayo Clinic Quantitative Imaging Network site, the Colon Cancer Family Registry and the Polyp Prevention Study.