What lies beneath? Diffusion EAP-based study of brain tissue microstructure

• Published in: Medical image analysis Vol. 32; pp. 145 - 156
• Main Authors: Zucchelli, Mauro, Brusini, Lorenza, Andrés Méndez, C., Daducci, Alessandro, Granziera, Cristina, Menegaz, Gloria
• Format: Journal Article
• Language: English
• Published: Netherlands Elsevier B.V 01-08-2016
• Subjects: 3D-SHORE; Axons; Brain - anatomy & histology; Brain - cytology; Brain - diagnostic imaging; Brain - pathology; Diffusion Magnetic Resonance Imaging - methods; Diffusion MRI; DSI; EAP; Healthy Volunteers; Humans; Image Enhancement - methods; Image Processing, Computer-Assisted - methods; Microstructure; NODDI; Sensitivity and Specificity; Stroke - diagnostic imaging; Stroke - pathology; 3D-SHORE; NODDI; Diffusion MRI; DSI; Microstructure; EAP
• ISSN: 1361-8415; 1361-8423
• DOI: 10.1016/j.media.2016.03.008

•The aim of this study is to characterize how EAP indices values change in different tissue microstructure configurations.•We calculate analytically EAP-derived RTOP, RTAP, and RTPP for 3D-SHORE basis.•EAP indices appear to be sensitive to variation in intracellular volume fraction and axons orientation dispersion, but not to axon diameter in simulated data.•In-vivo comparison with NODDI-derived microstructural indices confirm these results for a healthy subject.•Results on stroke patient highlight the feasibility of the EAP indices to characterize pathological condition in brain tissues.
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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.