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Platform for Quantitative Evaluation of Spatial Intratumoral Heterogeneity in Multiplexed Fluorescence Images

机译:定量荧光图像中空间瘤内异质性定量评估的平台

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摘要

We introduce THRIVE (Tumor Heterogeneity Research Interactive Visualization Environment), an open-source tool developed to assist cancer researchers in interactive hypothesis testing. The focus of this tool is to quantify spatial intratumoral heterogeneity (ITH), and the interactions between different cell phenotypes and non-cellular constituents. Specifically, we foresee applications in phenotyping cells within tumor microenvironments, recognizing tumor boundaries, identifying degrees of immune infiltration and epithelial/stromal separation, and identification of heterotypic signaling networks underlying microdomains. The THRIVE platform provides an integrated workflow for analyzing whole slide immunofluorescence images (WSFIs) and tissue microarrays, including algorithms for segmentation, quantification, and heterogeneity analysis. THRIVE promotes flexible deployment, a maintainable code base using open-source libraries, and an extensible framework for customizing algorithms with ease. THRIVE was designed with highly multiplexed immunofluorescence images in mind, and, by providing a platform to efficiently analyze high-dimensional immunofluorescence signals, we hope to advance these data toward mainstream adoption in cancer research.
机译:我们介绍了THRIVE(肿瘤异质性研究交互式可视化环境),这是一种开放源代码工具,旨在帮助癌症研究人员进行交互式假设检验。该工具的重点是量化空间肿瘤内异质性(ITH),以及不同细胞表型与非细胞成分之间的相互作用。具体而言,我们预见到在肿瘤微环境内的表型细胞中的应用,识别肿瘤边界,识别免疫浸润程度和上皮/基质分离以及识别微结构域下的异型信号网络。 THRIVE平台提供了用于分析整个玻片免疫荧光图像(WSFI)和组织微阵列的集成工作流程,其中包括用于分割,量化和异质性分析的算法。 THRIVE提倡灵活的部署,使用开源库的可维护代码库以及可轻松自定义算法的可扩展框架。 THRIVE的设计考虑了高度复用的免疫荧光图像,并且通过提供有效分析高维免疫荧光信号的平台,我们希望将这些数据推向癌症研究的主流。

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