CT IMAGING OF BLOOD VESSEL IN TRANSGENIC MOUSE MODELS FOR HUMAN TUMORS

人类肿瘤转基因小鼠模型中血管的 CT 成像

• 批准号: 7957217
• 负责人: CHRISTOPHER R. JOHNSON
• 金额: $ 9.02万
• 依托单位: UNIVERSITY OF UTAH
• 依托单位国家: 美国
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-08-01 至 2010-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7957217
• 关键词: Animals; Biomedical Computing; Blood; Blood Vessels; Blood Volume; Caliber; Collaborations; Computer Retrieval of Information on Scientific Projects Database; Contrast Media; Funding; Grant; Guidelines; Human; Image; Imagery; Institution; Life; Magnetic Resonance Imaging; Methods; Mus; Research; Research Personnel; Resources; Scanning; Source; Therapy Clinical Trials; Time; Transgenic Mice; United States National Institutes of Health; Visual; X-Ray Computed Tomography; angiogenesis; density; instrument; mouse model; pre-clinical; tool; tumor

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. Small animal X-ray computed tomography (microCT) is an economical and highly quantitative three-dimensional method for visualizing blood vessels and angiogenesis preclinically, even in comparison to small animal magnetic resonance imaging. In this collaboration, we are developing practical guidelines for rapid, accurate visualization of intermediate to large caliber (greater than 93 micron) blood vessels for serial assessment of vascularity during preclinical therapeutic trials in living mice. Because of the long scan times for most small animal computed tomography instruments, we are using a long-acting blood pool contrast agent. In addition to guidelines, we are also further developing tools to assess vessels through qualitative visual renderings. The same optimized acquisition settings will be necessary for segmentation analysis and will allow quantitative analysis of tumor blood volume, vessel density, vessel caliber, degree of branching, and tortuosity.

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