Our overall goal is to develop, optimize, and validate innovative and improved MRI techniques for the diagnosis, early detection, treatment monitoring, and investigation of neurodegenerative diseases (ND), which will be made available to the scientific community. These techniques will provide increased signal and contrast to noise and resolution per unit scan time, reduced susceptibility and motion artifacts, in order to improve disease detection. The techniques include improved MRI/MRS acquisition, image reconstruction methods, and processing/analysis methods for high magnetic field MRI/MRS. The results will be distributed to the scientific community. This proposal represents a continuation of collaborative work between MRI physicists, computer scientists and clinical investigators aimed at a single theme: neurodegenerative diseases.
The specific aims of this Biotechnology Research Resource are to develop, optimize and validate: 1) MR acquisition methods for structural, perfusion, and diffusion spectrum MRI, and spectroscopic imaging. The focus of the work will be on developing new sequences to capture alterations of brain structure, physiology (blood flow), and metabolism with improved sensitivity and resolution and increased reliability and precision. 2) Image reconstruction methods for increasing speed, efficiency, and quantitative accuracy of MRI. The focus of the work will be on exploiting the properties of Bayesian prior information for either deterministic or statistical image modeling to improve image quality, signal-to-noise and resolution. 3) MR image processing techniques for extraction of accurate and reproducible anatomical information. The focus of the work will be on developing novel tissue segmentation techniques and new spatial normalization strategies. 4) We will utilize these improvements in collaborative/service projects concerning NDs 5) We will provide training for investigators and staff within and outside the Research Resource. 6) We will disseminate the knowledge, tools, and data generated by this resource The significance of this project is several fold: First, the prevalence of NDs is rapidly growing due to aging of the population and methods for early detection are urgently needed. Second, due to advances in basic knowledge, treatments for NDs are under development and sensitive methods to determine treatment response are required. This Research Resource will develop improved techniques for clinical diagnosis, early detection, and monitoring of progression and treatment effects of common NDs, and these technical advances will also be applicable to many other clinical problems.

Agency
National Institute of Health (NIH)
Institute
National Center for Research Resources (NCRR)
Type
Biotechnology Resource Grants (P41)
Project #
3P41RR023953-02S1
Application #
7891998
Study Section
Special Emphasis Panel (ZRG1-SBIB-J (40))
Program Officer
Levy, Abraham
Project Start
2009-08-24
Project End
2011-08-23
Budget Start
2009-08-24
Budget End
2011-08-23
Support Year
2
Fiscal Year
2009
Total Cost
$999,850
Indirect Cost
Name
Northern California Institute Research & Education
Department
Type
DUNS #
613338789
City
San Francisco
State
CA
Country
United States
Zip Code
94121
Kuceyeski, A; Shah, S; Dyke, J P et al. (2016) The application of a mathematical model linking structural and functional connectomes in severe brain injury. Neuroimage Clin 11:635-647
Lam, Fan; Liu, Ding; Song, Zhuang et al. (2016) A fast algorithm for denoising magnitude diffusion-weighted images with rank and edge constraints. Magn Reson Med 75:433-40
Pannetier, Nicolas A; Stavrinos, Theano; Ng, Peter et al. (2016) Quantitative framework for prospective motion correction evaluation. Magn Reson Med 75:810-6
Kuceyeski, Amy; Navi, Babak B; Kamel, Hooman et al. (2016) Structural connectome disruption at baseline predicts 6-months post-stroke outcome. Hum Brain Mapp 37:2587-601
Friedman, Eric J; Young, Karl; Tremper, Graham et al. (2015) Directed network motifs in Alzheimer's disease and mild cognitive impairment. PLoS One 10:e0124453
Kuceyeski, Amy; Navi, Babak B; Kamel, Hooman et al. (2015) Exploring the brain's structural connectome: A quantitative stroke lesion-dysfunction mapping study. Hum Brain Mapp 36:2147-60
Ma, Chao; Liang, Zhi-Pei (2015) Design of multidimensional Shinnar-Le Roux radiofrequency pulses. Magn Reson Med 73:633-45
Zhao, Bo; Lu, Wenmiao; Hitchens, T Kevin et al. (2015) Accelerated MR parameter mapping with low-rank and sparsity constraints. Magn Reson Med 74:489-98
Lu, Zhao-Hua; Zhu, Hongtu; Knickmeyer, Rebecca C et al. (2015) Multiple SNP Set Analysis for Genome-Wide Association Studies Through Bayesian Latent Variable Selection. Genet Epidemiol 39:664-77
Raj, Ashish; LoCastro, Eve; Kuceyeski, Amy et al. (2015) Network Diffusion Model of Progression Predicts Longitudinal Patterns of Atrophy and Metabolism in Alzheimer's Disease. Cell Rep :

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