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Abstract #2359

An Automated Method to Optimize the Contrast of Small Structures

Ryan Chamberlain1, Thomas M. Wengenack2, Joseph F. Poduslo2, Clifford R. Jack3, Michael Garwood1

1Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, MN, United States; 2Departments of Neurology, Neuroscience, and Biochemistry/Molecular Biology, Mayo Clinic College of Medicine, Rochester, MN, United States; 3Department of Radiology, Mayo Clinic College of Medicine, Rochester, MN, United States

Many MRI applications require visualizing structures on the order of a few pixels in size. In these applications the CNR ratio of the small structures is more important than the SNR of the image. The CNR can be affected dramatically by the image resolution relative to the size of the structure, but the exact relation of resolution and CNR depends on the specific structure and pulse sequence. This work describes an automated method to determine the acquired image resolution to optimize the CNR of small structures. It is demonstrated as applied to imaging amyloid plaques in transgenic mouse models of Alzheimer's disease.