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Small Animal Cancer Imaging

$223,473P30FY2019CANIH

Washington University, Saint Louis MO

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Abstract

THIS COMPONENT IS ENTITLED THE SMALL ANIMAL CANCER IMAGING SHARED RESOURCE ABSTRACT Project Summary/Abstract With the revolution in molecular biology, transgenic animal models ? in particular mice ? have become an indispensable part of the cancer research armamentarium. The Alvin J. Siteman Cancer Center's Small-Animal Cancer Imaging (SACI) Shared Resource (initially established under the auspices of the NCI's Small-Animal Imaging Resource Program) addresses the need for nondestructive imaging and analysis of small-animal laboratory models of cancer. It provides state-of-the-art facilities and infrastructure for magnetic resonance imaging, positron emission tomography, X-ray computed tomography, single-photon emission computed tomography, and optical (including Cerenkov) imaging of mice, rats and other small laboratory animals that serve as models of cancer. SACI combines instrumental and intellectual capabilities found at few other institutions and serves a broad community of cancer scientists who have a pressing need for quantitative image analysis of small- animal model systems. The principal function of SACI is to provide access to and maintenance of small- animal magnetic resonance, nuclear medicine, and optical imaging scanners for cancer research. In addition to supporting cancer research applications of small-animal imaging, SACI also provides research and development at the frontier of imaging technology in an effort to make the most powerful new imaging strategies available to its community of users. The shared resource is organized around three modality-specific imaging components: (i) nuclear medicine, (ii) magnetic resonance, and (iii) optical. An overarching goal is translation to the clinic of imaging and therapy agents and protocols developed and validated with small-animal models; thus, SACI directly supports the mission of the Siteman Cancer Center by supporting basic discovery cancer research and cancer imaging protocols with translational potential.

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