title: Kurtosis analysis of neural diffusion organization.
abstract: A computational framework is presented for relating the kurtosis tensor for water diffusion in brain to tissue models of brain microstructure. The tissue models are assumed to be comprised of non-exchanging compartments that may be associated with various microstructural spaces separated by cell membranes. Within each compartment the water diffusion is regarded as Gaussian, although the diffusion for the full system would typically be non-Gaussian. The model parameters are determined so as to minimize the Frobenius norm of the difference between the measured kurtosis tensor and the model kurtosis tensor. This framework, referred to as kurtosis analysis of neural diffusion organization (KANDO), may be used to help provide a biophysical interpretation to the information provided by the kurtosis tensor. In addition, KANDO combined with diffusional kurtosis imaging can furnish a practical approach for developing candidate biomarkers for neuropathologies that involve alterations in tissue microstructure. KANDO is illustrated for simple tissue models of white and gray matter using data obtained from healthy human subjects.
authors.affiliation: Department of Diagnostic Radiology, The University of Hong Kong, Pokfulam, Hong Kong. Electronic address: edward.s.hui@gmail.com.
authors.forename: Edward S
authors.initials: ES
authors.lastname: Hui
authors.affiliation: Center for Biomedical Imaging, Medical University of South Carolina, Charleston, SC, USA; Department of Neurosciences, Medical University of South Carolina, Charleston, SC, USA. Electronic address: glenng@musc.edu.
authors.forename: G
authors.initials: G
authors.lastname: Russell Glenn
authors.affiliation: Center for Biomedical Imaging, Medical University of South Carolina, Charleston, SC, USA; Department of Neurosciences, Medical University of South Carolina, Charleston, SC, USA; Department of Radiology and Radiological Science, Medical University of South Carolina, Charleston, SC, USA. Electronic address: helpern@musc.edu.
authors.forename: Joseph A
authors.initials: JA
authors.lastname: Helpern
authors.affiliation: Center for Biomedical Imaging, Medical University of South Carolina, Charleston, SC, USA; Department of Radiology and Radiological Science, Medical University of South Carolina, Charleston, SC, USA. Electronic address: jense@musc.edu.
authors.forename: Jens H
authors.initials: JH
authors.lastname: Jensen
mesh_terms: D000328:Adult; D001369:Axons / Q000502:physiology; D001921:Brain / Q000033:anatomy & histology* / Q000502:physiology*; D003198:Computer Simulation; D003627:Data Interpretation, Statistical; D004058:Diffusion; D038524:Diffusion Magnetic Resonance Imaging / Q000379:methods*; D056324:Diffusion Tensor Imaging / Q000379:methods*; D006801:Humans; D008297:Male; D008875:Middle Aged; D008959:Models, Neurological; D015233:Models, Statistical; D016008:Statistical Distributions; D014867:Water / Q000378:metabolism; D066127:White Matter / Q000502:physiology
chemical_list: D014867:Water
keywords: Diffusion; Kurtosis; MRI; Microstructure; Tissue model