Olympus NanoZoomer RS Whole Slide Imaging System

描述(由申请人提供)：我们建议购买奥林巴斯NanoZomer数字病理幻灯片成像系统，带有荧光显微镜附件，以支持罗切斯特大学医学中心至少26名由NIH资助的研究人员。在人类疾病的实验模型中，对人类和动物的良性和恶性组织的薄片进行显微分析是许多研究的共同终点。组织样本的分析通常始于对玻片上石蜡包埋的H&E染色切片的显微镜评估，以区分正常和病理过程，然后分析进一步的切片，用特殊的组织化学或免疫组织化学(IHC)分析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和另一种细胞类型，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取代的程度。这些组织的各种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。其他分析包括对冰冻切片或石蜡切片的荧光显微镜或荧光原位杂交(FISH)。这些方法的一个缺点是IHC染色和荧光会随着时间的推移而褪色，并且在分析过程中荧光会被猝灭。因此，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并存储图像将是当前方法的一大进步。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需要时间来准确评分组织切片，特别是随着蛋白质组和基因组研究中出现更多目标蛋白，以及组织微阵列的使用越来越多。这在我们机构的许多翻译研究中产生了瓶颈，这将通过共享整个幻灯片图像分析系统来解决。这项提议的长期目标是提供一种最先进的设备和技术支持，以自动扫描载玻片，目的是帮助研究人员更快地实现他们的科学目标，并比URMC现有的设备更快、更准确地产生分析数据。NIH资助的46个项目将得到支持，涵盖范围广泛的疾病，包括免疫学、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载片；2)将这些图像存储一段规定的时间，直到调查人员捕获它们；3)培训调查人员使用NanoZomer的形态测量功能，使他们能够对存储的图像进行形态计量分析，构建3D图像，并将存储的图像与其他设备(如CT或MRI)从标本处理成石蜡之前获取的图像进行匹配。这些努力应该会加快调查人员的研究，帮助他们更快地获得新的数据，目的是帮助他们撰写新的提案，从而在市建局创造新的就业机会。

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.