title: What lies beneath? Diffusion EAP-based study of brain tissue microstructure.
abstract: Diffusion weighted magnetic resonance signals convey information about tissue microstructure and cytoarchitecture. In the last years, many models have been proposed for recovering the diffusion signal and extracting information to constitute new families of numerical indices. Two main categories of reconstruction models can be identified in diffusion magnetic resonance imaging (DMRI): ensemble average propagator (EAP) models and compartmental models. From both, descriptors can be derived for elucidating the underlying microstructural architecture. While compartmental models indices directly quantify the fraction of different cell compartments in each voxel, EAP-derived indices are only a derivative measure and the effect of the different microstructural configurations on the indices is still unclear. In this paper, we analyze three EAP indices calculated using the 3D Simple Harmonic Oscillator based Reconstruction and Estimation (3D-SHORE) model and estimate their changes with respect to the principal microstructural configurations. We take advantage of the state of the art simulations to quantify the variations of the indices with the simulation parameters. Analysis of in-vivo data correlates the EAP indices with the microstructural parameters obtained from the Neurite Orientation Dispersion and Density Imaging (NODDI) model as a pseudo ground truth for brain data. Results show that the EAP derived indices convey information on the tissue microstructure and that their combined values directly reflect the configuration of the different compartments in each voxel.
authors.affiliation: Department of Computer Science, University of Verona, Verona, Italy. Electronic address: mauro.zucchelli@univr.it.
authors.forename: Mauro
authors.initials: M
authors.lastname: Zucchelli
authors.affiliation: Department of Computer Science, University of Verona, Verona, Italy.
authors.forename: Lorenza
authors.initials: L
authors.lastname: Brusini
authors.affiliation: Department of Computer Science, University of Verona, Verona, Italy.
authors.forename: C
authors.initials: C
authors.lastname: Andrés Méndez
authors.affiliation: Swiss Federal Institute of Technology (EPFL) Lausanne, Lausanne, Switzerland.
authors.forename: Alessandro
authors.initials: A
authors.lastname: Daducci
authors.affiliation: Department of Clinical Neurosciences, CHUV and University of Lausanne, Lausanne, Switzerland.
authors.forename: Cristina
authors.initials: C
authors.lastname: Granziera
authors.affiliation: Department of Computer Science, University of Verona, Verona, Italy.
authors.forename: Gloria
authors.initials: G
authors.lastname: Menegaz
mesh_terms: D001369:Axons; D001921:Brain / Q000033:anatomy & histology / Q000166:cytology / Q000000981:diagnostic imaging* / Q000473:pathology; D038524:Diffusion Magnetic Resonance Imaging / Q000379:methods*; D064368:Healthy Volunteers; D006801:Humans; D007089:Image Enhancement / Q000379:methods*; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D012680:Sensitivity and Specificity; D020521:Stroke / Q000000981:diagnostic imaging / Q000473:pathology
keywords: 3D-SHORE; DSI; Diffusion MRI; EAP; Microstructure; NODDI