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)是一种利用激活的T细胞诱导靶向的肿瘤治疗。 对癌症的免疫反应。临床前IMT研究一直受到限制，因为没有 对包括卵巢在内的小鼠模型中T细胞生物分布进行纵向成像的有效方法 癌症。这是一个迫切的未得到满足的需求，因为监测激活的T细胞的唯一可行方法， 免疫组织化学和流式细胞术，都是终末的和体外的。小鼠的全身光学成像 模型能够在体内监测荧光标记的T细胞，但光被强烈衰减 在鼠标表面拍摄的组织和图像取决于光学组织属性， 动物的大小和姿势。也没有可用的解剖学参考资料来提供一种方法 所需的器官描述和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)描述高度依赖于操作员 且耗时长，导致数据重现性差、可变性强。因此，InVivo Analytics寻求资金开发InVivoFLUOR，这是一款3D荧光自动数据分析工具 小鼠模型的断层扫描(Flt)。它由：(1)符合动物模型的身体模型(BCAM)和 用于动物几何和空间配准的多视点透照FLT和空间配准的镜架 (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模拟的分布；以及(3)与操作员无关的分布 ROI描述和分类工具，用于利用固有数据进行图像数据分析 BCAM提供的一致性。在目标1中，我们将改进多视角成像的Flt工具，并 启用不同大小的动物之间的图像联合配准。在目标2中，我们将开发一种自动化的 ROI描述和分类工具，用于产生独立于操作员的、定量的和 研究结果具有可重复性。在目标3中，我们将自动分析荧光标记的T细胞 并将其与播散性卵巢肿瘤的3D生物发光图进行联合注册。这个 能够即时量化T细胞在同一动物体内的纵向分布，而不是 在每个时间点处死一只不同的动物，通过流式细胞仪或组织学进行T细胞计数，两者都不是 它可以识别被激活的T细胞可能“隐藏”的位置，对 新的高精度IMTS的发展和结果。InVivoFluor将成为我们InVivoAX的一部分 平台，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设备，在全球拥有3,000台安装量。它 将实现跨平台数据比较和分析，消除依赖于操作员的可变性， 增加数据的再现性，并将促进新疗法的翻译。