This project advances the state-of-the-art in High-Angular Resolution Diffusion Imaging (HARDI), a powerful new imaging approach that can resolve fiber pathways in the brain with spectacular precision. Uniting expertise at an NIH-funded National Neuroimaging Resource (at UCLA), the University of Minnesota Center for Magnetic Resonance Research, and Siemens Corporate Research, we aim to demonstrate that HARDI provides new and vital information in assessing clinically important brain degeneration in HIV/AIDS and Alzheimer's Disease (AD), extending our initial findings that revealed how these diseases spread dynamically in the living brain. HARDI applies magnetic field gradients to the brain, in up to 256 different directions, to precisely detail the directions, pathways, and integrity of fibers in the brain. HARDI datasets cannot yet be compared across subjects without new mathematics that treats these signals as lying in Riemannian manifolds. This project provides those tools. Our research will (1) advance the mathematics - based in part on geometry, statistics, and Riemannian manifolds - to extract information from HARDI, and (2) quantify how much HARDI can improve our understanding of brain degeneration, and what factors affect it. Using the extra detail in HARDI images, we will develop a method to enable large-scale multi-subject comparison of HARDI images, by fluidly aligning 3D images across subjects (Aim 1;Multi-subject Alignment). This is the first step towards population studies of disease, e.g., comparing fiber integrity across patient populations to examine gene or treatment effects, or comparing a patient with a normative database. Validation on phantoms and synthetic data is a key part of all Aims.
In Aim 2 (Segmentation and Connectivity Mapping), we will develop algorithms to map white matter connectivity, and identify clinically important fiber pathways in the brain, based on the full angular information of HARDI.
In Aim 3 (HARDI Statistics), optimized voxel-based statistics will compare HARDI data, point-by-point, across populations, to identify systematic fiber deficits, comparing fiber integrity and connectivity with a normal reference population.
In Aim 4 (HARDI Maps of Brain Degeneration), we will evaluate HARDI for revealing new descriptors of AD and HIV-related brain degeneration: two illnesses on which we have published prolifically, where measures of white matter degeneration are sorely lacking. The societal burden of AD and HIV is growing;HIV affects 40 million people worldwide, and AD affects 4.5 million individuals in the U.S. alone;everyone is at risk. Our powerful markers of brain white matter degeneration will help us determine how much benefit HARDI's added resolution provides. This new analytic approach will greatly advance our ability to understand pathological brain degeneration, providing sensitive new measures to track it. This has immediate value for drug trials and patient monitoring. As always, we will share all algorithms, protocols, and images, with 50+ collaborating laboratories.

Public Health Relevance

This project develops tools that unleash the full power of HARDI (high-angular resolution diffusion imaging) to advance clinical studies of the brain. HARDI applies magnetic field gradients to the brain in up to 256 different directions to precisely detail the directions, pathways, and integrity of fibers and their connections. We will evaluate HARDI for understanding and revealing new descriptors of Alzheimer's Disease and HIV-related brain white matter degeneration - with immediate value for drug trials and patient monitoring in HIV, which affects 40 million people worldwide, and in AD, which affects 4.5 million individuals in the U.S. alone.

Agency
National Institute of Health (NIH)
Institute
National Institute of Biomedical Imaging and Bioengineering (NIBIB)
Type
Research Project (R01)
Project #
5R01EB008432-04
Application #
8323086
Study Section
Biomedical Imaging Technology Study Section (BMIT)
Program Officer
Pai, Vinay Manjunath
Project Start
2009-09-30
Project End
2014-08-31
Budget Start
2012-09-01
Budget End
2014-08-31
Support Year
4
Fiscal Year
2012
Total Cost
$642,666
Indirect Cost
$108,885
Name
University of California Los Angeles
Department
Neurology
Type
Schools of Medicine
DUNS #
092530369
City
Los Angeles
State
CA
Country
United States
Zip Code
90095
Daianu, Madelaine; Mendez, Mario F; Baboyan, Vatche G et al. (2016) An advanced white matter tract analysis in frontotemporal dementia and early-onset Alzheimer's disease. Brain Imaging Behav 10:1038-1053
Farooq, Hamza; Xu, Junqian; Nam, Jung Who et al. (2016) Microstructure Imaging of Crossing (MIX) White Matter Fibers from diffusion MRI. Sci Rep 6:38927
Daianu, Madelaine; Mezher, Adam; Mendez, Mario F et al. (2016) Disrupted rich club network in behavioral variant frontotemporal dementia and early-onset Alzheimer's disease. Hum Brain Mapp 37:868-83
Franke, Barbara; Stein, Jason L; Ripke, Stephan et al. (2016) Genetic influences on schizophrenia and subcortical brain volumes: large-scale proof of concept. Nat Neurosci 19:420-31
Dennis, Emily L; Jin, Yan; Kernan, Claudia et al. (2015) WHITE MATTER INTEGRITY IN TRAUMATIC BRAIN INJURY: EFFECTS OF PERMISSIBLE FIBER TURNING ANGLE. Proc IEEE Int Symp Biomed Imaging 2015:930-933
Daianu, Madelaine; Jahanshad, Neda; Nir, Talia M et al. (2015) Rich club analysis in the Alzheimer's disease connectome reveals a relatively undisturbed structural core network. Hum Brain Mapp 36:3087-103
Demir, Ali; Çetingül, H Ertan (2015) Sequential Hierarchical Agglomerative Clustering of White Matter Fiber Pathways. IEEE Trans Biomed Eng 62:1478-89
Daianu, Madelaine; Jacobs, Russell E; Weitz, Tara M et al. (2015) Multi-Shell Hybrid Diffusion Imaging (HYDI) at 7 Tesla in TgF344-AD Transgenic Alzheimer Rats. PLoS One 10:e0145205
Jahanshad, Neda; Nir, Talia M; Toga, Arthur W et al. (2015) Seemingly unrelated regression empowers detection of network failure in dementia. Neurobiol Aging 36 Suppl 1:S103-12
Dennis, Emily L; Jin, Yan; Villalon-Reina, Julio E et al. (2015) White matter disruption in moderate/severe pediatric traumatic brain injury: advanced tract-based analyses. Neuroimage Clin 7:493-505

Showing the most recent 10 out of 133 publications