Rapid Cancer-Treatment Efficacy Monitoring System

癌症治疗疗效快速监测系统

• 批准号: 6643057
• 负责人: SAYAN PATHAK
• 金额: $ 9.96万
• 依托单位: INSIGHTFUL CORPORATION
• 依托单位国家: 美国
• 财政年份: 2003
• 资助国家: 美国
• 起止时间: 2003-04-01 至 2004-03-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/6643057
• 关键词: apoptosis; artificial intelligence; automated health care system; bioimaging /biomedical imaging; biomedical automation; computer program /software; fluorescence microscopy; image processing; leukemia; patient care management; prognosis; technology /technique development; tissue /cell culture

DESCRIPTION (provided by applicant): Evaluating cancer therapy efficacy by studying symptomatic improvement in patient condition is a popular practice due to the lack of rapid, reliable and robust quantitative evaluation protocols for routine clinical measurement of cancer therapy efficacy. Reducing time required for arriving at decisions and reducing cost without compromising accuracy could provide potentially improved treatments especially for patients with advanced leukemia of various types. This proposal focuses on rapid quantitative assessment of cancer treatment efficacy for leukemia. The proposed approach is based on quantifying apoptosis (programmed cell death) and has been shown to be one of the most reliable and one of the earliest indicators for assessing anticancer efficacy of a drug. Several other techniques are available to detect apoptosis (Agarose gel electrophoresis, Caspase-3, TUNEL assay, Morphological estimation, Annexin V assays etc). However, these techniques are inaccurate, expensive or time consuming. A recently developed a two stage DNA diffusion assay holds promise to be an accurate, relatively inexpensive and rapid methodology for quantitative apoptosis measurement via the apoptotic index. The two stages are:(1) slide preparation and microscopy imaging, which requires approximately 1.5 hrs and (2) image analysis, which is tedious, and takes approximately 2 hours of additional intensive manual labor leading to errors in categorization of the cells. We propose to fully automate the second stage with the goal to minimize manual effort and there by reduce the human errors. This would also make the procedure more reproducible. Phase I work will involve: (1) segmentation and classification algorithm development for automatic apoptotic index calculation, and (2) characterizing the algorithm performance by inducing apoptosis in leukemia cells in culture using known apoptosis inducing agents.

描述（由申请人提供）：由于缺乏快速、可靠和稳健的常规临床测量癌症治疗功效的定量评估方案，通过研究患者病情的症状改善来评估癌症治疗功效是一种流行的做法。在不影响准确性的情况下减少做出决策所需的时间并降低成本可以提供潜在的改进治疗，特别是对于患有各种类型的晚期白血病的患者。该提案的重点是快速定量评估癌症对白血病的治疗效果。所提出的方法基于量化细胞凋亡（程序性细胞死亡），并已被证明是评估药物抗癌功效的最可靠和最早的指标之一。其他几种技术可用于检测细胞凋亡（琼脂糖凝胶电泳、Caspase-3、TUNEL 测定、形态学估计、膜联蛋白 V 测定等）。然而，这些技术不准确、昂贵或耗时。 最近开发的两阶段 DNA 扩散测定有望成为一种通过细胞凋亡指数定量细胞凋亡测量的准确、相对便宜且快速的方法。这两个阶段是：(1) 载玻片制备和显微镜成像，需要大约 1.5 小时；(2) 图像分析，这是乏味的，需要大约 2 小时的额外密集体力劳动，导致细胞分类错误。我们建议使第二阶段完全自动化，目标是最大限度地减少手动工作，从而减少人为错误。这也将使该过程更具可重复性。第一阶段的工作将涉及：（1）开发用于自动凋亡指数计算的分割和分类算法，以及（2）通过使用已知的凋亡诱导剂诱导培养物中的白血病细胞凋亡来表征算法性能。