title: Evaluating kurtosis-based diffusion MRI tissue models for white matter with fiber ball imaging.
abstract: In order to quantify well-defined microstructural properties of brain tissue from diffusion MRI (dMRI) data, tissue models are typically employed that relate biological features, such as cell morphology and cell membrane permeability, to the diffusion dynamics. A variety of such models have been proposed for white matter, and their validation is a topic of active interest. In this paper, three different tissue models are tested by comparing their predictions for a specific microstructural parameter to a value measured independently with a recently proposed dMRI method known as fiber ball imaging (FBI). The three tissue models are all constructed with the diffusion and kurtosis tensors, and they are hence compatible with diffusional kurtosis imaging. Nevertheless, the models differ significantly in their details and predictions. For voxels with fractional anisotropies (FAs) exceeding 0.5, all three are reasonably consistent with FBI. However, for lower FA values, one of these, called the white matter tract integrity (WMTI) model, is found to be in much better accord with FBI than the other two, suggesting that the WMTI model has a broader range of applicability.
authors.affiliation: Department of Radiology and Radiological Science, Medical University of South Carolina, Charleston, South Carolina, USA.|Center for Biomedical Imaging, Medical University of South Carolina, Charleston, South Carolina, USA.
authors.forename: Jens H
authors.initials: JH
authors.lastname: Jensen
authors.affiliation: Department of Radiology and Radiological Science, Medical University of South Carolina, Charleston, South Carolina, USA.|Center for Biomedical Imaging, Medical University of South Carolina, Charleston, South Carolina, USA.|Department of Neurology, Medical University of South Carolina, Charleston, South Carolina, USA.
authors.forename: Emilie T
authors.initials: ET
authors.lastname: McKinnon
authors.affiliation: Department of Radiology and Radiological Science, Medical University of South Carolina, Charleston, South Carolina, USA.|Center for Biomedical Imaging, Medical University of South Carolina, Charleston, South Carolina, USA.|Department of Neuroscience, Medical University of South Carolina, Charleston, South Carolina, USA.
authors.forename: G Russell
authors.initials: GR
authors.lastname: Glenn
authors.affiliation: Department of Radiology and Radiological Science, Medical University of South Carolina, Charleston, South Carolina, USA.|Center for Biomedical Imaging, Medical University of South Carolina, Charleston, South Carolina, USA.|Department of Neurology, Medical University of South Carolina, Charleston, South Carolina, USA.|Department of Neuroscience, Medical University of South Carolina, Charleston, South Carolina, USA.
authors.forename: Joseph A
authors.initials: JA
authors.lastname: Helpern
mesh_terms: D001921:Brain / Q000166:cytology / Q000000981:diagnostic imaging* / Q000502:physiology; D003198:Computer Simulation; D038524:Diffusion Magnetic Resonance Imaging / Q000379:methods*; D056324:Diffusion Tensor Imaging / Q000379:methods*; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D008959:Models, Neurological; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D066127:White Matter / Q000166:cytology / Q000000981:diagnostic imaging* / Q000502:physiology
keywords: MRI; brain; diffusion; fiber ball imaging; kurtosis; tensor; tissue model; white matter