Diffusion tensor imaging (DTI), with its sensitivity to microscopic variations in diffusion anisotropy (DA) in neural tissues, has generated great interest in both basic neuroscience research and clinical applications as a method that offers the potential for the non-invasive assessment of the status of neural tissue architecture. However, the standard DTI methodology, including its high angular resolution (HARDI) extensions, which utilizes a single pair of pulsed field gradients (sPFG), are predicated on the existence of voxel compositions that exhibit a macroscopic DA on the scale of the imaging resolution. This is often the case with voxels containing bundles of white matter (WM) fibers and thus DTI in WM has become a major focus of DTI research and applications. However, this is not the case in gray matter (GM) which is microscopically heterogeneous but lacks the structural coherence on the spatial scale of voxels to exhibit macroscopic DA. This has severely limited our ability to utilize the sensitivity of MRI to diffusion in the investigation of GM microstructure, which is a tissue of significant clinical interest. Recently, a novel set of MR methods based upon the double pulsed field gradient (dPFG) pairs have been investigated theoretically and verified in simple experiments to exhibit sensitivity to microscopic DA in voxels that are macroscopically homogeneous. These studies have primarily been applied to materials with microscopic pores, reflecting the focus on porous materials from which these methods developed. However, while we hypothesize that these methods have great potential for the study of GM, the great complexity of this tissue makes investigation of dPFG methods in GM nearly impossible to do analytically. Thus the goal of this proposal is to utilize our recently developed diffusion simulation platform (DiffSim), in conjunction with our recently developed theoretical framework for dPFG, to investigate the ability of dPFG methods to detect and quantitate gray matter architectural parameters and changes, and develop experimental techniques for applying these methods clinically.

Public Health Relevance

While diffusion tensor imaging (DTI) is a magnetic resonance imaging (MRI) technique that offers the potential for the non-invasive assessment of neural tissue structure, its usage is predicated on the existence of neuronal fibers with macroscopic organization on the scale of imaging resolution;thus its application has been almost exclusively to white matter (WM) structure and disease, to the exclusion of gray matter (GM), which is macroscopically incoherent, despite being microscopically coherent. Recently, however, a new class of diffusion sensitive MRI methods, called double pulsed field gradient (dPFG) MRI, has demonstrated a unique sensitivity to microscopically coherent tissues and thus may have an enormous impact on a wide range of clinical and basic research applications related to GM. Our goal is to use our sophisticated diffusion MRI simulation platform DiffSim to augment our theoretical studies of dPFG in GM to develop practical implementations in humans and thus provide the basis for clinical techniques that provide consistent and meaningful measurements of GM architecture and physiology.

National Institute of Health (NIH)
National Institute of Mental Health (NIMH)
Research Project (R01)
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Special Emphasis Panel (ZRG1-NT-L (09))
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Freund, Michelle
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University of California San Diego
Schools of Medicine
La Jolla
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Galinsky, Vitaly L; Martinez, Antigona; Paulus, Martin P et al. (2018) Joint Estimation of Effective Brain Wave Activation Modes Using EEG/MEG Sensor Arrays and Multimodal MRI Volumes. Neural Comput 30:1725-1749
Lewalle, Alexandre; Land, Sander; Carruth, Eric et al. (2018) Decreasing Compensatory Ability of Concentric Ventricular Hypertrophy in Aortic-Banded Rat Hearts. Front Physiol 9:37
Berry, David B; Regner, Benjamin; Galinsky, Vitaly et al. (2018) Relationships between tissue microstructure and the diffusion tensor in simulated skeletal muscle. Magn Reson Med 80:317-329
Galinsky, Vitaly L; Frank, Lawrence R (2017) A Unified Theory of Neuro-MRI Data Shows Scale-Free Nature of Connectivity Modes. Neural Comput 29:1441-1467
Berry, David B; You, Shangting; Warner, John et al. (2017) * A 3D Tissue-Printing Approach for Validation of Diffusion Tensor Imaging in Skeletal Muscle. Tissue Eng Part A 23:980-988
Frank, Lawrence R; Galinsky, Vitaly L (2016) Dynamic Multiscale Modes of Resting State Brain Activity Detected by Entropy Field Decomposition. Neural Comput 28:1769-811
Galinsky, Vitaly L; Frank, Lawrence R (2016) The Lamellar Structure of the Brain Fiber Pathways. Neural Comput :1-24
Frank, Lawrence R; Galinsky, Vitaly L (2016) Detecting Spatio-Temporal Modes in Multivariate Data by Entropy Field Decomposition. J Phys A Math Theor 49:
Yopak, Kara E; Galinsky, Vitaly L; Berquist, Rachel M et al. (2016) Quantitative Classification of Cerebellar Foliation in Cartilaginous Fishes (Class: Chondrichthyes) Using Three-Dimensional Shape Analysis and Its Implications for Evolutionary Biology. Brain Behav Evol 87:252-64
Sorg, Scott F; Schiehser, Dawn M; Bondi, Mark W et al. (2016) White Matter Microstructural Compromise Is Associated With Cognition But Not Posttraumatic Stress Disorder Symptoms in Military Veterans With Traumatic Brain Injury. J Head Trauma Rehabil 31:297-308

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