ULTRAFAST MORPHOLOGY WORKSTATION FOR CANCER DIAGNOSIS

用于癌症诊断的超快形态学工作站

• 批准号: 3506942
• 负责人: KENDALL PRESTON
• 金额: $ 24.58万
• 依托单位: KENSAL CORPORATION
• 依托单位国家: 美国
• 财政年份: 1993
• 资助国家: 美国
• 起止时间: 1993-03-12 至 1995-02-28
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/3506942
• 关键词: artificial intelligence; biomedical equipment development; breast neoplasm /cancer diagnosis; cell cycle; charge coupled device camera; clinical biomedical equipment; computer assisted diagnosis; computer program /software; computer system design /evaluation; digital imaging; female; histopathology; human tissue; image processing; immunologic techniques; microscopy; morphology; neoplasm /cancer classification /staging; neoplasm /cancer diagnosis; nonHodgkin's lymphoma; personal computers; prognosis; stainings; video recording system

The goal was to translate into commercial practice research by a team at Carnegie Mellon University (CMU) and the University of Southern California (USC) in automating the subtyping of follicular cancer of the lymph node by computerized microscopy. This solves the problem that visual subtyping (observing follicular cells through the microscope and scoring them as small, mixed, or large) is so inaccurate that 30% of the time the treatment plan recommended for the patient is wrong. With about 35,000 individuals developing such cancers annually in the USA each year and this number increasing yearly due to AIDS, the implication was that thousands of patients were receiving the wrong treatment. In the 1980s CMU demonstrated that a version of the $150,000 Coulter Biomedical diff3/50 robot image-analyzing microscope controlled by a minicomputer could subtype with an accuracy of about 2%. In the Phase I proposal the PI suggested a demonstration where the CMU methodology would be moved to a low-cost, PC-based workstation and tested using a new multimode, multicolor camera jointly developed by the Pathology Imaging Corp. and Kensal Consulting (KSC). This was done, 1200 images were digitized and analyzed, and the new workstation divided the small-cell-large-cell continuum into five regions (small, small/mixed, mixed, etc.) with a repeatability of 95.5%. However, the computer time required per specimen was one hour - too slow for convenient clinical use. This Phase II proposal is for funding to accelerate this process 1000 fold by creating and commercializing a for use by the DoD on the SDI program. It is also proposed to demonstrate that the same workstation will analyze cells in immuno-stained breast tumor tissue at almost flow cytometry rates (2000 cells per second) for use in determining the proliferative index.

其目标是将一个团队的研究转化为商业实践， 卡内基梅隆大学（CMU）和南方大学 加州（南加州大学）在自动化的滤泡癌的亚型， 淋巴结，通过计算机显微镜。 这解决了以下问题， 视觉分型（通过显微镜观察滤泡细胞， 将它们分为小、混合或大）是如此不准确， 为患者推荐的治疗方案是错误的。 与约 在美国，每年有35，000人患上这种癌症 由于艾滋病，这个数字每年都在增加，这意味着， 成千上万的病人接受了错误的治疗。 1980年代 CMU证明，价值15万美元的库尔特生物医学公司的一个版本 用小型计算机控制的diff 3/50机器人图像分析显微镜 能以2%的准确率进行分型 在第一阶段提案中， PI建议进行一个示范，将CMU方法移至 一个低成本的，基于PC的工作站，并使用新的多模式测试， 由病理成像公司和 Kensal Consulting（KSC）. 完成后，1200张图像被数字化， 分析，新的工作站将小细胞大细胞 连续体分为五个区域（小型、小型/混合、混合等）与 重复性为95.5%。 然而，每个样本所需的计算机时间 一个小时-太慢了，不方便临床使用。 这项II期 一项提议是通过建立一个新的基金来加速这一进程1000倍。 并将其商业化，供国防部用于SDI计划。 也是 建议证明，同一工作站将分析细胞， 免疫染色乳腺肿瘤组织在几乎流式细胞术率（2000 细胞/秒）用于测定增殖指数。