Automatic Stereology of Biological Tissue Using 3-D VCS

使用 3-D VCS 进行生物组织的自动体视学

• 批准号: 7197343
• 负责人: PETER Randolph MOUTON
• 金额: $ 19.07万
• 依托单位: STEREOLOGY RESOURCE CENTER, INC.
• 依托单位国家: 美国
• 财政年份: 2003
• 资助国家: 美国
• 起止时间: 2003-07-10 至 2008-02-29
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7197343
• 关键词: 3-Dimensional; Algorithms; Area; Arts; Ballistics; Biological; Cells; Classification; Color; Data Collection; Disease Management; Documentation; Fluorescence; Goals; Gold; Health; Image Analysis; Investigation; Length; Manuals; Microscopic; Numbers; Phase; Procedures; Proliferating; Proteins; Reaction; Relative (related person); Research; Research Personnel; Resources; Sales; Sampling; Signal Transduction; Solid; Spatial Distribution; Staging; Staining and Labeling; Staining method; Stains; Standards of Weights and Measures; Surface; System; Three-dimensional analysis; Time; Tissues; Variant; base; computerized; cost; interest; programs; response; size; systems research; tissue processing

DESCRIPTION (provided by applicant): The studies in Phase II continue the effort begun in Phase I to equip a commercially available stereology system (Stereologer) with image analysis capability to automatically sample and quantify features of biological interest in tissue sections. The investigators have adapted image analysis algorithms, developed in part by a collaborator's missile ballistic systems research program, into an auto-detection and auto-analysis program called Verified Computerized Stereoanalysis (VCS). Phase I demonstrated the ability of VCS to quantify size parameters of proliferating cells in tissue sections with equal accuracy to the gold standard (manual click) approach, but with a significant 8-fold improvement in throughput efficiency. Operationally, the VCS program acquires an internal target of color pixels associated with the feature of interest, while the user performs manual data collection for the first section from the initial case in the study. Once the user verifies an acceptable level of accuracy relative to manual data collection (gold standard), the program can be switched into fully automatic mode, a combination of motorized stage control for systematic-random sampling; auto-detection of stained microscopic features of interest; and, auto-analysis of global and local size parameters and their variation based on state-of-the-art stereological principles. These investigations found that biological features that label (stain) proteins with specific immunological-based probes, followed by amplification of the signal with chromogen reactions or fluorescence, stimulate the most robust response from the VCS algorithm. Phase II will expand VCS to the 3-D analysis of all 1st-order (number, length, surface area, and volume) and 2nd-order (variation, spatial distribution) stereological parameters (Aim 1); validate 3-D VCS against the gold standard approach and identify the principal tissue processing and staining procedures to increase algorithm robustness (Aim 2); and, develop StereoTutorials and on-line documentation to assist the conversion of current users of computerized stereology systems from manual to automatic VCS approaches (Aim 3). The long-term goal for VCS is to increase the throughput efficiency for stereoanalyses of parameters on tissue sections without a loss of accuracy; reduce research costs in terms of time and labor; and, accelerate scientific progress toward improvements in health and the management of disease. Solid evidence that the PI and colleagues can successfully commercialize the VCS program in Phase III is demonstrated by worldwide sales and support of the Stereologer and other stereology resources for the past decade.

描述（由申请人提供）：第二阶段的研究继续第一阶段开始的努力，为市售体视学系统（Stereologer）配备图像分析功能，以自动采样和量化组织切片中生物感兴趣的特征。研究人员将图像分析算法（部分由合作者的导弹弹道系统研究项目开发）改编成自动检测和自动分析程序，称为“验证计算机立体分析”（VCS）。第一阶段证明了 VCS 能够量化组织切片中增殖细胞的大小参数，其精度与金标准（手动点击）方法相同，但吞吐量效率显着提高 8 倍。在操作上，VCS 程序获取与感兴趣的特征相关的颜色像素的内部目标，而用户则从研究中的初始案例的第一部分执行手动数据收集。一旦用户验证了相对于手动数据收集（黄金标准）的可接受的准确度水平，程序就可以切换到全自动模式，这是系统随机采样的电动阶段控制的组合；自动检测感兴趣的染色微观特征；并且，基于最先进的体视学原理自动分析全局和局部尺寸参数及其变化。这些研究发现，用特定的基于免疫学的探针标记（染色）蛋白质，然后用​​发色反应或荧光放大信号的生物学特征，刺激了 VCS 算法最强烈的响应。第二阶段将 VCS 扩展到所有一阶（数量、长度、表面积和体积）和二阶（变化、空间分布）体视参数的 3-D 分析（目标 1）；根据金标准方法验证 3-D VCS，并确定主要的组织处理和染色程序，以提高算法的稳健性（目标 2）；开发立体教程和在线文档，以帮助计算机体视学系统的当前用户从手动 VCS 方法转换为自动 VCS 方法（目标 3）。 VCS 的长期目标是在不损失准确性的情况下提高组织切片参数立体分析的吞吐量效率；降低时间和劳动力方面的研究成本；并加速科学进步，以改善健康和疾病管理。 Stereologer 和其他体视学资源在过去十年的全球销售和支持证明了 PI 及其同事能够在第三阶段成功将 VCS 项目商业化的有力证据。