Ophthalmic imaging of small animal models of ocular diseases

眼部疾病小动物模型的眼科成像

• 批准号: 7512280
• 负责人: Shuliang Jiao
• 金额: $ 2.64万
• 依托单位: UNIVERSITY OF MIAMI SCHOOL OF MEDICINE
• 依托单位国家: 美国
• 财政年份: 2008
• 资助国家: 美国
• 起止时间: 2008-09-05 至 2008-10-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7512280
• 关键词: 3-Dimensional; Algorithms; Animal Model; Animals; Anterior; Area; Cells; Collaborations; Control Animal; Cornea; Data; Defect; Development; Disease; Disease Progression; Edema; Eye; Feedback; Genetic; Glaucoma; Goals; Histology; Image; Institutes; Invasive; Keratoplasty; Longitudinal Studies; Maps; Measurement; Modeling; Monitor; Mus; Numbers; Optic Nerve; Optical Coherence Tomography; Optics; Play; Productivity; Public Health; Rattus; Research; Research Personnel; Resolution; Retina; Retinal; Retinal Neoplasms; Retinoblastoma; Rodent Model; Role; Scientist; Speed; Staging; Structure; Study Subject; System; Techniques; Technology; Testing; Thick; Time; Tumor Volume; base; design; desire; ganglion cell; high throughput technology; in vivo; interest; mouse model; novel; outcome forecast; research study; retinal nerve fiber layer; tomography; tool; treatment effect; tumor growth; ultra high resolution

DESCRIPTION (provided by applicant): Small animal models play an irreplaceable role in the study of ocular diseases, but the need for structural information at different stages of a disease leads to time-consuming histology, inefficient use of animals, and large variability. Our long-term objective is to develop a high throughput testing facility that provides quantitative, non-invasive, high resolution, structural imaging of animal models of ophthalmic diseases. By high throughput we mean the acquisition of images and the extraction of desired information as efficiently and rapidly as possible, thereby maximizing the scientific yield of the facility. The facility will use a novel investigator-controlled animal alignment system that allows rapid selection of the imaged retinal areas together with ultra-high resolution spectral-domain OCT (optical coherence tomography) to provide 3D retinal images. To evaluate disease-induced damage and progression and to monitor treatment effects, the cell layers of the retina will be quantified using 3D segmentation of the OCT images. This project promises to significantly reduce the number of animals needed to achieve many research objectives. Collaborating scientists using small animal models for their research will provide valuable feedback to enhance the facility's productivity. The specific aims of the proposed research are to: 1. Design and build a novel animal alignment system together with a slit lamp biomicroscope based ultra-high resolution spectral-domain OCT and robust interchangeable optical probes for high throughput imaging of the anterior segment and retina of small animals. The animal alignment system that allows rapid selection of the imaging areas of interest. 2. Develop 3-D segmentation algorithms for (1) automatic segmentation of the RNFL of the retina and (2) automatic segmentation of the boundaries of retinal tumor. These algorithms will provide quantitative information (e.g., RNFL thickness maps and tumor volume) about the change that occurs at different stages of a disease. 3. Apply the system and algorithms to studying animal models of ocular diseases. We will first focus on three rodent models: (1) we will image changes in retinal structure in a rat glaucoma model, including changes of optic nerve and RNFL thickness at different stages of glaucoma damage; (2) We will quantitatively evaluate progression and treatment effect in a mouse model of retinoblastoma; (3) We will study the status and prognosis of a murine model of corneal transplant. PUBLIC HEALTH RELEVANCE: The proposed research will provide a powerful tool that will greatly accelerate the research on ocular diseases like glaucoma, retinoblastoma, and corneal transplant. It promises not only to reduce the number of animals required but also possible longitudinal studies that are currently impossible to conduct.

描述（由申请人提供）：小动物模型在眼部疾病的研究中具有不可替代的作用，但由于疾病不同阶段对结构信息的需求，导致组织学耗时长，动物利用效率低，变异性大。我们的长期目标是开发一种高通量测试设备，为眼科疾病的动物模型提供定量、非侵入性、高分辨率的结构成像。通过高通量，我们指的是尽可能高效和快速地获取图像和提取所需信息，从而最大限度地提高设备的科学产量。该设施将使用一种新的研究人员控制的动物校准系统，该系统可以快速选择成像的视网膜区域，并使用超高分辨率光谱域OCT（光学相干断层扫描）提供3D视网膜图像。为了评估疾病引起的损伤和进展并监测治疗效果，将使用OCT图像的3D分割对视网膜的细胞层进行量化。该项目有望显著减少实现许多研究目标所需的动物数量。利用小动物模型进行研究的合作科学家将提供有价值的反馈，以提高该设施的生产力。提出的研究的具体目的是：1。结合裂隙灯生物显微镜的超高分辨率光谱域OCT和强大的可互换光学探针，设计并构建一种新的动物对准系统，用于小动物前段和视网膜的高通量成像。动物定位系统，允许快速选择感兴趣的成像区域。2. 开发三维分割算法，实现(1)视网膜RNFL的自动分割和(2)视网膜肿瘤边界的自动分割。这些算法将提供关于疾病不同阶段发生的变化的定量信息（例如，RNFL厚度图和肿瘤体积）。3. 将该系统和算法应用于眼部疾病动物模型的研究。我们将首先重点研究三种啮齿动物模型：(1)我们将对大鼠青光眼模型视网膜结构的变化进行成像，包括青光眼损伤不同阶段视神经和RNFL厚度的变化；(2)我们将定量评估视网膜母细胞瘤小鼠模型的进展和治疗效果；(3)研究小鼠角膜移植模型的现状及预后。公共卫生相关性：本研究将为加速青光眼、视网膜母细胞瘤、角膜移植等眼部疾病的研究提供有力的工具。它不仅有望减少所需动物的数量，而且还可能进行目前无法进行的纵向研究。