Section: New Results

From DW-MRI to Fiber Pathways and Microstructures Recovery

Mapping Average axon diameters under long diffusion time

Participants : Gonzalo Sanguinetti, Rachid Deriche.

This work proposes an original method to recover axon diameter distribution (ADD) parameters using nuclear magnetic resonance. White matter (WM) is modelled as a bi-compartmental medium composed of an intra axonal space where the diffusion is restricted and an extra axonal space where diffusion is hindered. Under the assumption of long diffusion time, we provide a novel and efficient model for the component of the signal due to the restricted part. This technique might be interpreted as an interesting simplification of the AxCaliber framework, which leads to a simpler model and an extremely faster acquisition protocol. To test and validate our method, we use the open-source toolkit Camino for computing Monte-Carlo simulations of NMR data and model the WM as 3D cubic environments, formed by parallel cylinders with gamma distributed radii. Promising experimental results illustrate the potential of the proposed method.

This work has been submitted to ISBI'2014 and accepted for presentation and publication.

NMR characterization of cylinder radii distribution using a SHORE-based regularization method.

Participants : Gonzalo Sanguinetti, Daniel Alexander [Centre for Medical Image Computing, Dept. Computer Science, UCL] , Matt Hall [Centre for Medical Image Computing, Dept. Computer Science, UCL] , Rachid Deriche.

In this work, we extend the framework presented by Ozarslan et al [79] by adding a regularization term for better measuring the moments of a cylinder radii distribution by means of NMR acquisitions. The added value of the regularization term is tested and validated using Monte Carlo simulations of NMR signals from complex white matter-like environment. The open source toolkit CAMINO [50] is used for computing the simulations and an excellent agreement is obtained between the ground truth and the estimated moments.

This work has been submitted to ISMRM'2014.

Quantitative comparison of reconstruction methods for intra-voxel fiber recovery from diffusion MRI

Participants : Emmanuel Caruyer [SBIA, University of Pennsylvania Medical School, USA] , Sylvain Merlet, Rachid Deriche.

In diffusion MRI, a technique known as diffusion spectrum imaging reconstructs the propagator with a discrete Fourier transform, from a Cartesian sampling of the diffusion signal. Alternatively, it is possible to directly reconstruct the orientation distribution function in q-ball imaging, providing so-called high angular resolution diffusion imaging. In between these two techniques, acquisitions on several spheres in q-space offer an interesting trade-off between the angular resolution and the radial information gathered in diffusion MRI. A careful design is central in the success of multishell acquisition and reconstruction techniques and the design of acquisition in multishell is still an open and active field of research.

In this work, we propose a novel method to design sampling schemes with optimal angular coverage and show the positive impact on angular resolution in diffusion MRI. Our method is based on a generalization of electrostatic repulsion to multishell and allows to design multishell acquisition with uniform angular coverage.

We evaluated the impact of our method using simulations, on the angular resolution in one and two bundles of fiber configurations. Compared to more commonly used radial sampling, we show that our method improves the angular resolution, as well as fiber crossing discrimination.

This work has been published in [16] .

Choosing tractography parameters to improve connectivity mapping

Participants : Gabriel Girard [SCIL Lab., Sherbrooke University] , Kevin Whittingstall [SCIL Lab., Sherbrooke University] , Kevin Whittingstall [SCIL Lab., Sherbrooke University] , Rachid Deriche.

Diffusion-weighted imaging (DWI) is often used as a starting point for in vivo white matter (WM) connectivity to reconstruct potential WM pathways between brain areas. Tractography algorithms have many parameters which can influence reconstruction and connectivity. Various choices of parameters have been proposed. But how does one choose the best set of parameters ? In this study, we varied three critical parameters while monitoring connectivity score using the Tractometer evaluation system on the International Symposium on Biomedical Imaging (ISBI) Challenge synthetic dataset. The three parameters were: The maximum deviation angle between two consecutive tractography steps (this addresses the hypothesis of smoothness of the WM pathways), the spherical function (SF) threshold (this aims at removing noisy propagation directions during the tractography process) and the initial SF threshold (this aims at removing initial noise at the seeds and to start tractography in a good tangent direction to the WM bundle).

This work has been submitted to ISMRM'2014.

Improved tractography using structural priors

Participants : Gabriel Girard [SCIL Lab., Sherbrooke University] , Maxime Descoteaux [SCIL Lab., Sherbrooke University] , Kevin Whittingstall [SCIL Lab., Sherbrooke University] , Rachid Deriche.

In this work, we propose better tractography parameters in term of global connectivity and a novel tractography stopping criterion based on partial volume estimation maps, calculated from a T1-weighted image. We also propose a particle filtering method using anatomical information as prior for tractography to enforce streamlines connecting gray matter regions and reducing the proportion of erroneous streamlines. Results show streamlines more uniformly distributed among long and short, and small and large white matter bundles. This provides connectivity estimation not underestimated for bundles having higher complexity. Quantitative analysis is done on synthetic datasets and qualitative results are shown on real data. The proposed method takes advantage of prior information on the brain to change the dMRI-based tracking direction and help providing streamlines that can quantify the brain structure.

This on-going work will be submitted to NeuroImage.

From diffusion MRI to brain connectomics

Participants : Aurobrata Ghosh, Rachid Deriche.

Diffusion MRI (dMRI) is a unique modality of MRI which allows one to indirectly examine the microstructure and integrity of the cerebral white matter in vivo and non-invasively. Its success lies in its capacity to reconstruct the axonal connectivity of the neurons, albeit at a coarser resolution, without having to operate on the patient, which can cause radical alterations to the patient's cognition. Thus dMRI is beginning to assume a central role in studying and diagnosing important pathologies of the cerebral white matter, such as Alzheimer's and Parkinson's diseases, as well as in studying its physical structure in vivo. In this work, we present an overview of the mathematical tools that form the framework of dMRI – from modelling the MRI signal and measuring diffusion properties, to reconstructing the axonal connectivity of the cerebral white matter, i.e., from Diffusion Weighted Images (DWIs) to the human connectome.

This work has been published in [38] .