Fluorescence tomography plugin unit for spatial monitoring of T cell migration

用于 T 细胞迁移空间监测的荧光断层扫描插件单元

• 批准号: 10264164
• 负责人: Alexander D. Klose
• 金额: $ 96.92万
• 依托单位: IN VIVO ANALYTICS, INC.
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-09-17 至 2024-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10264164
• 关键词: 3-Dimensional; Algorithms; Anatomy; Animal Model; Animals; Antitumor Response; Area Under Curve; Attenuated; Biodistribution; Biological Sciences; Bioluminescence; Biotechnology; Cancer Model; Cell Count; Classification; Computer software; Consumption; Data; Data Analyses; Development; Diffuse; Drug Industry; Fluorescence; Funding; Generations; Geometry; Goals; Histology; Image; Imaging Device; Immune Targeting; Immune response; Immunohistochemistry; Immunologic Markers; Immunotherapy; Industry; Institution; Knowledge; Label; Letters; Ligands; Light; Location; Longitudinal Studies; Malignant Neoplasms; Malignant neoplasm of ovary; Manuals; Maps; Methods; Modeling; Molds; Monitor; Mus; Optics; Organ; Outcome; Phase; Preclinical Testing; Probability; Prognosis; Property; ROC Curve; Recovery; Reporting; Reproducibility; Research; Research Personnel; Services; Shapes; Site; Source; Surface; T-Lymphocyte; Three-Dimensional Image; Time; Tissue imaging; Tissues; Transillumination; Translations; Treatment outcome; Weight; animal tissue; automated analysis; base; cancer cell; cancer therapy; cell motility; cloud based; commercial application; cost; density; fluorescence imaging; image reconstruction; image registration; imaging system; improved; in vivo; in vivo monitoring; interest; mouse model; novel; novel therapeutics; optical imaging; ovarian neoplasm; pre-clinical; preclinical imaging; reconstruction; serial imaging; software as a service; therapy development; tomography; tool; tumor

Immunotherapy (IMT) is a cancer treatment that harnesses activated T cells to induce a targeted immune response against cancer. Preclinical IMT research has been limited because there are no effective methods to longitudinally image T cell biodistributions in mouse models, including ovarian cancer. This is an urgent unmet need because the only viable methods to monitor activated T cells, immunohistochemistry and FACs, are both terminal and ex vivo. Whole-body optical imaging of mouse models enables in vivo monitoring of fluorescence-labeled T cells, but light is strongly attenuated by tissue and images taken at the mouse surface are dependent on the optical tissue properties, the animal’s size and pose. There also is no anatomical reference available that could provide a means for required organ delineation along with T cell biodistribution analysis. In addition, manual Region-Of- Interest (ROI) delineation of fluorescence images for further data analysis is highly operator-dependent and time-consuming, resulting in poor data reproducibility and high variability. Therefore, InVivo Analytics seeks funding to develop InVivoFLUOR, an automated data analysis tool for 3D fluorescence tomography (FLt) of mouse models. It is comprised of: (1) a Body Conforming Animal Mold (BCAM) and mirror gantry for multi-view transillumination FLt and spatial registration of the animal’s geometry and pose; (2) an Organ Probability Map (OPM) for providing an organ template and optical tissue parameter distributions for biodistribution analysis and light propagation modeling; and (3) an operator-independent ROI delineation and classification tool for image data analysis that capitalizes on the inherent data congruency provided by the BCAM. In Aim 1, we will improve the FLt tool for multi-view imaging and enable image co-registration across animals with different size. In Aim 2, we will develop an automated ROI delineation and classification tool for producing operator-independent, quantitative, and reproducible study results. In Aim 3, we will automatically analyze fluorescence-labeled T cell biodistributions and co-register them to 3D bioluminescence maps of disseminated ovarian tumors. The ability to instantaneously quantify the T cell distribution in the same animal longitudinally, as opposed to sacrificing a different animal at every time point for T cell counting via FACs or histology, neither of which can identify sites where the activated T cells may be “hiding”, has a significant impact on the development and outcome of new IMTs with high accuracy. InVivoFLUOR will be part of our InVivoAX platform, a cloud-based Software-as-a-Service (SaaS), and will be sold to the pharmaceutical industry and research institutions as add-on to imaging systems with an installed base >3,000 units worldwide. It will enable cross-platform data comparison and analysis, eliminate operator-dependent variability, increase data reproducibility, and will facilitate the translation of new therapeutics.

免疫疗法（IMT）是一种癌症治疗，其利用活化的T细胞来诱导靶向免疫应答。 对癌症的免疫反应。临床前IMT研究受到限制，因为没有 在小鼠模型中纵向成像T细胞生物分布的有效方法，包括卵巢 癌这是一个迫切的未满足的需求，因为唯一可行的方法来监测活化的T细胞， 免疫组织化学和FACs的方法是终末和离体的。小鼠全身光学成像 模型能够在体内监测荧光标记的T细胞，但光被强烈衰减， 在小鼠表面拍摄的组织和图像取决于光学组织特性， 动物的大小和姿势也没有可用的解剖学参考，可以提供一种方法， 需要器官描绘沿着T细胞生物分布分析。此外，手动区域- 用于进一步数据分析的荧光图像的兴趣（ROI）描绘高度依赖于操作员 并且耗时，导致数据再现性差和变异性高。因此，Invivo Analytics寻求资金开发InVivoFLUOR，这是一种用于3D荧光的自动数据分析工具 小鼠模型的断层扫描（FLt）。它由以下组成：（1）符合人体的动物模型（BCAM）和 - 用于多视图透照FLt和动物几何形状的空间配准的反射镜机架， 姿势;（2）器官概率图（OPM），用于提供器官模板和光学组织参数 用于生物分布分析和光传播建模的分布;以及（3）独立于操作员的 利用固有数据进行图像数据分析的ROI描绘和分类工具 BCAM提供的一致性。在目标1中，我们将改进用于多视图成像的FLt工具， 实现不同大小动物的图像配准。在目标2中，我们将开发一个自动化的 ROI描绘和分类工具，用于生成独立于操作员的、定量的 可重复的研究结果。在目标3中，我们将自动分析荧光标记的T细胞， 生物分布，并将其与播散性卵巢肿瘤的3D生物发光图配准。的 能够纵向地即时量化同一动物中的T细胞分布，而不是 在每个时间点处死不同的动物，通过FACs或组织学进行T细胞计数， 它可以识别激活的T细胞可能“隐藏”的部位，对免疫系统有显著影响。 高精度新型IMT的开发和结果。InVivoFLUOR将成为我们InVivoAX的一部分 平台，一个基于云的软件即服务（SaaS），并将出售给制药行业 和研究机构作为成像系统的附加组件，全球安装量超过3，000台。它 将实现跨平台数据比较和分析，消除操作员依赖的可变性， 增加数据的可重复性，并将促进新疗法的转化。