This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. Primary support for the subproject and the subproject's principal investigator may have been provided by other sources, including other NIH sources. The Total Cost listed for the subproject likely represents the estimated amount of Center infrastructure utilized by the subproject, not direct funding provided by the NCRR grant to the subproject or subproject staff. Overview: The overall goal of this project is to develop new pulse sequences and methods for quantitative structural and perfusion MRI in support of research projects and clinical applications of the Resource Center, which focuses on imaging of neurodegenerative diseases. Most neurodegenerative diseases are associated with subtle and slowly progressing alterations in the brain that are often difficult to detect with MRI. A major focus of this project is the development of improved structural MRI methods that provide enhanced tissue contrast for more precise measurements of brain tissue degeneration and loss, such as regional cortical thinning. Another major focus is the development of better methods for quantification of brain perfusion as a means to determine brain physiology and function in neurodegenerative conditions.
Specific aim 1 :
The aim i s to develop concepts of variable contrast-weighted imaging (VTI) for the enhancement of spatial resolution in structural MRI. The vast majority of structural MRI studies of the brain rely on T1 or/and T2 weighting for image contrast. However, the accurate representation of brain tissue boundaries based on T1 and T2 alone has limitations, because the relaxation properties of gray matter and white matter partially overlap. To overcome these limitations, aim 1 focuses on multi-acquisition variable T1-weighted imaging in conjunction with T1 estimations by least-squares fits with spatial priors to improve image contrast and accuracy in delineating tissue boundaries. Extension of aim 1 (Administrative Supplement): The extension of aim 1 aims to integrate diffusion-weighting into high-resolution structural MRI, complementing the T1 contrast. Specifically, the new aim is designed to 1) develop high resolution structural MRI with joined T1 and diffusion weighting for improved measurements of boundaries and surfaces of brain structures and 2) extend diffusion weighting by diffusion correlation weighting that imprints a new diffusion contrast on high resolution MRI. Toward these goals, high resolution MPRAGE with spiral k-space readout will be developed as part of a subcontract. The extension of aim 1 was possible through administrative supplements.
Specific aim 2 :
The aim i s to develop methods for better quantification of cerebral blood flow and estimations of water transfer into the brain based on arterial spin labeling (ASL) MRI. In particular, the objective is to evaluate variations in both T1 and T2 relaxation of the ASL signal to characterize brain physiology and function as reflected by water transfer into the brain. Toward this goal, the aim will focus on modeling perfusion dynamics in dual-echo 3D GRASE data, as developed in project 2 that provide intrinsic measures of T1 and T2 relaxation of the ASL signal.

Agency
National Institute of Health (NIH)
Institute
National Center for Research Resources (NCRR)
Type
Biotechnology Resource Grants (P41)
Project #
5P41RR023953-04
Application #
8362774
Study Section
Special Emphasis Panel (ZRG1-SBIB-J (40))
Project Start
2011-07-01
Project End
2012-06-30
Budget Start
2011-07-01
Budget End
2012-06-30
Support Year
4
Fiscal Year
2011
Total Cost
$189,594
Indirect Cost
Name
Northern California Institute Research & Education
Department
Type
DUNS #
613338789
City
San Francisco
State
CA
Country
United States
Zip Code
94121
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
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 :
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
Kuceyeski, A F; Vargas, W; Dayan, M et al. (2015) Modeling the relationship among gray matter atrophy, abnormalities in connecting white matter, and cognitive performance in early multiple sclerosis. AJNR Am J Neuroradiol 36:702-9

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