Olympus NanoZoomer RS Whole Slide Imaging System

描述（由申请人提供）：我们拟购买一台Olympus NanoZoomer数字病理学载玻片成像系统（带荧光显微镜附件），以支持罗切斯特大学医学中心至少26名NIH资助的研究者。在人类疾病的实验模型中，对来自人类和动物的良性和恶性组织的薄切片进行显微镜分析是许多研究的共同终点。组织样本的分析通常始于载玻片上石蜡包埋的H& E染色切片的显微镜评估，以区分正常与病理过程，然后分析用特殊组织化学或免疫组织化学（IHC）测定染色的进一步切片，以检测单个细胞中的酶活性或特定蛋白质。这些检测有助于区分一种细胞类型，识别不同类型的癌症，并评估炎症的严重程度或正常组织的破坏程度及其被修复组织替代的程度。组织的这些不同特征的定量分析可以使用耗时、劳动密集型的方法和各种图像分析系统来完成。其他分析包括冷冻或石蜡切片上的荧光显微镜或荧光原位杂交（FISH）。这些方法的缺点是IHC染色和荧光随时间而褪色，并且荧光在分析期间被淬灭。因此，由其他人随后进行分析以确认解释可能是困难的或不可能的。自动扫描这些类型的幻灯片和存储的图像将是一个很大的进步，目前的方法。研究蛋白质和基因表达的另一个主要挑战是训练有素的人员准确评分组织切片所需的时间，特别是随着蛋白质组学和基因组研究中更多靶蛋白的出现，以及组织微阵列的使用越来越多。这在我们机构的许多转化研究中产生了瓶颈，这将通过共享整个载玻片图像分析仪系统来解决。该提案的长期目标是提供最先进的设备和技术支持，以自动扫描载玻片，旨在帮助研究人员更快地达到他们的科学目标，并比URMC目前可用的设备更快，更准确地生成分析数据。美国国立卫生研究院资助的46个项目涵盖了广泛的疾病，包括免疫、肌肉骨骼、肺、前列腺和神经肌肉良性和恶性疾病。具体目标是：1）扫描来自广泛研究的组织切片; 2）将这些图像存储一段规定的时间，直到研究者捕获这些图像; 3）培训研究人员使用NanoZoomer的形态测量功能，使他们能够对存储的图像进行形态测量分析，构建3D图像，并将存储的图像与使用其他设备（如CT或MRI）获取的图像进行匹配，从标本中提取的DNA这些努力应该加速调查人员的研究，帮助他们更快地获得新数据，目的是帮助他们编写新的提案，从而在URMC创造新的就业机会。

DESCRIPTION (provided by applicant): We propose to purchase an Olympus NanoZoomer Digital Pathology slide imaging system with a fluorescence microscopy attachment to support at least 26 NIH funded investigators at the University of Rochester Medical Center. Microscopic analysis of thin sections of benign and malignant tissues from humans and from animals in experimental models of human diseases is a common end-point of many research studies. Analysis of tissue samples typically begins with microscopic assessment of paraffin-embedded H&E-stained sections on glass slides to distinguish normal from pathologic processes, followed by analysis of further sections stained with special histochemical or immunohistochemical (IHC) assays to detect enzymatic activity or particular proteins in individual cells. These assays help distinguish one cell type from another, identify different types of cancers, and assess the severity of inflammation or the extent of destruction of normal tissues and their replacement by repair tissue. Quantitative analysis of these various features of tissues can be done using time-consuming, labor-intensive methods and various image analysis systems. Other analyses include fluorescence microscopy or fluorescence in-situ hybridization (FISH) on frozen or paraffin sections. A drawback of these methods is that IHC staining and fluorescence fades with time and fluorescence is quenched during analysis. Thus, subsequent analysis by others to confirm an interpretation may be difficult or impossible. Automatic scanning of these types of slides and storage of the images would be a great advance over current methods. Another major challenge in studies examining protein and gene expression is the time it takes trained personnel to accurately score tissue sections, especially with the advent of more target proteins from proteomic and genomic studies, and the increasing use of tissue microarrays. This has produced a bottleneck in many translational research studies at our institution, which would be solved by having a shared whole slide image analyzer system. The long-term objective of this proposal is to provide a state-of-the-art device and technical support to scan glass slides automatically with the aim of helping researchers reach their scientific goals faster and produce analytic data more quickly and accurately than is possible with equipment currently available at URMC. The 46 NIH-funded projects to be supported cover a wide array of disorders, including immunologic, musculoskeletal, pulmonary, prostatic, and neuromuscular benign and malignant diseases. The Specific Aims are to 1) Scan slides of tissues from a broad range of studies; 2) Store these images for a defined period until they are captured by investigators; 3) Train investigators to use the NanoZoomer's morphometric capabilities to allow them to carryout morphometric analysis on the stored images, construct 3-D images and match stored images with those acquired using other devices, such as <CT or MRI, from specimens before they were processed into paraffin. These efforts should accelerate the research of investigators and help them get new data faster, with the goal of assisting them to write new proposals and thus generate new jobs at URMC.