Diseases of the central nervous system (CNS) are a significant public health and economic problem, affecting one in three Americans at some point in life, and costing over $500 billion per year. Pathologically, the white matter (WM) is compromised in CNS disorders by neuro-inflammatory processes (gliosis, astrocytosis, macrophage infiltration), acute axonal beading, and neurodegenerative processes (demyelination, axonal degeneration and loss). While axonal degeneration results in irreversible disability, the roles of different inflammatory processes, and their interplay with neurodegeneration, are unknown, mainly due to the lack of biomarkers that parse these concurrent processes in vivo in humans. Our main objective is to distinguish and quantify neurodegenerative and inflammatory processes in WM with MRI, and evaluate them as prognostic markers for Multiple Sclerosis (MS), a chronic inflammatory and neurodegenerative disorder.
In Aim 1, we will develop a fast T2-weighted dMRI sequence unifying our TE-dependent Diffusion Imaging (TEdDI) technique with free gradient wave forms reducing acquisition time to within 15 minutes, and employ Cramer-Rao lower bound minimization to find an optimal protocol for estimating intra- and extra-axonal water fractions, diffusion coefficients and relaxation times, which are the proposed markers of neurodegeneration and inflammation. We will then test the protocol's accuracy and reproducibility on phantoms and volunteers.
In Aim 2, we will use our protocol to track neurodegeneration and inflammation both cross-sectionally and longitudinally on MS patients at different stages in the disease, and identify specific changes of all parameters with increasing disease severity. We expect that our neurodegeneration-related parameters will be more sensitive than lesion load and volumetrics in tracking disability. Furthermore, we will for the first time assess changes in compartmental diffusivities and relaxation times and relate them to MS disease progression.
In Aim 3, we will develop a framework of realistic Monte Carlo random walk simulations in WM geometries reconstructed from 3d electron microscopy. Ab initio, we will quantitatively explore the effect of gliosis, beading, demyelination and axonal loss in normal-appearing WM on diffusion and WM microstructure markers. Overall, the project will yield novel non-invasive clinically feasible diffusion MRI markers sensitive and specific to diffuse neurodegeneration and inflammatory processes, that could help better understand MS disease progression and open new avenues for effective management of patients and therapy development. The developed MRI pipeline for estimating WM microstructure markers will be straightforwardly extendable beyond MS, to help understand and quantify neurodegeneration and inflammation in other neurological diseases.

Public Health Relevance

Diseases of the central nervous system are a significant public health and economic problem, affecting one in three Americans at some point in life, and costing over $500 billion per year. The main objective of this proposal is to distinguish and quantify neurodegenerative and inflammatory processes in human white matter with MRI, and evaluate them as prognostic markers for multiple sclerosis. The developed MRI protocol for mapping white matter microstructure markers, together with realistic simulations of neurodegeneration and inflammation in normal appearing white matter, will yield novel non-invasive clinically feasible MR markers that could help gain insight into the role of neurodegeneration and inflammation MS, as well as and in other neurological diseases.

National Institute of Health (NIH)
National Institute of Neurological Disorders and Stroke (NINDS)
Research Project (R01)
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Emerging Imaging Technologies in Neuroscience Study Section (EITN)
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Utz, Ursula
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New York University
Schools of Medicine
New York
United States
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Lee, Hong-Hsi; Fieremans, Els; Novikov, Dmitry S (2018) What dominates the time dependence of diffusion transverse to axons: Intra- or extra-axonal water? Neuroimage 182:500-510
Kochunov, Peter; Dickie, Erin W; Viviano, Joseph D et al. (2018) Integration of routine QA data into mega-analysis may improve quality and sensitivity of multisite diffusion tensor imaging studies. Hum Brain Mapp 39:1015-1023
Veraart, Jelle; Novikov, Dmitry S; Fieremans, Els (2018) TE dependent Diffusion Imaging (TEdDI) distinguishes between compartmental T2 relaxation times. Neuroimage 182:360-369
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Chung, Sohae; Fieremans, Els; Wang, Xiuyuan et al. (2018) White Matter Tract Integrity: An Indicator of Axonal Pathology after Mild Traumatic Brain Injury. J Neurotrauma 35:1015-1020

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