TRADITIONAL POSTER - ismrm

Poster Sessions
1587. Challenges in Reconstructing the Propagator Via a Cumulant Expansion of the One-Dimensional Q-
Space MR Signal
Aurobrata Ghosh 1 , Evren Özarslan 2 , Rachid Deriche 3
1 Project Team Odyssée, INRIA Sophia Antipolis - Méditerannée, Sophia Antipolis , Alpes Maritimes, France; 2 Section on Tissue
Biophysics and Biomimetics, NICHD, National Institutes of Health, Bethesda, MD, United States; 3 INRIA Sophia Antipolis -
Méditerannée, rachid.deriche@sophia.inria.fr, Sophia Antipolis, Alpes Maritimes, France
We validate the GDTI with Gram-Charlier series approximation of the propagator approach in 1D, by comparing the Gram-Charlier and the Edgeworth
series on closed form diffusion propagators with known cumulants. We also compare against estimated cumulants. We conclude that the Edgeworth series
outperforms the Gram-Charlier series when the cumulants are known, but estimating the cumulants from the signal is numerically an important and sensitive
problem.
1588. Detecting Restriction Using Non-Parametric Modelling of Diffusion MR Data
Saad Jbabdi 1 , Karla Laureen Miller 1 , Adrian R. Groves
1 FMRIB Centre, University of Oxford, Oxford, United Kingdom
There is a growing interest in biophysical mechanisms for the diffusion contrast, with the exciting perspective of quantifying brain tissue microstructure (e.g.
axon size and density). In particular, modelling restriction effects in the signal allows us to estimate the size of restricting structures. It is not clear, however,
to what extent the signal acquired in vivo is sensitive to restriction. We suggest a non-parametric approach (no biophysical model assumed) to quantify
restriction effects in the diffusion data. This method can be used either as a diagnostic tool or for experimental design.
1589. Implementation of the Equilateral Triangle in the Multiple Correlation Function Approach as Model
Geometry for Restricted Diffusion.
Frederik Bernd Laun 1 , Bram Stieltjes
1 Medical Physics in Radiology, German Cancer Research Center, Heidelberg, Baden-Württemberg, Germany
The multiple correlation function approach uses the eigensystem of the Laplace operator to compute the effect of diffusion weighting gradients much more
efficiently than Monte-Carlo simulations. However the applicability is limited since the governing matrices could only be computed for few model systems.
Here we present the solutions for a further model system, the equilateral triangle. One interesting finding is that the apparent diffusion coefficient for this
confining geometry is not dependent on the gradient orientation for moderate b-values, while a clear orientation dependency is observed for high b-values.
1590. The Effect of Metric Selection on Averaging Diffusion Tensors – When and Why Do Tensors Swell?
Ofer Pasternak 1 , Nir Sochen 2 , Peter J. Basser 3
1 Brigham and Women's Hosptial, Harvard Medical School, Boston, MA, United States; 2 Tel Aviv University, Israel; 3 Section on
Tissue Biophysics & Biomimetics (STBB), National Institutes of Health (NIH), Bethesda, MD, United States
Metric selection is an essential step in performing diffusion tensor analysis, and here we investigate the selection effect on the estimation of FA, ADC and
volume of mean tensors. We use Monte-Carlo simulations to generate noisy replicates, and compare estimations using a Euclidean and a Log-Euclidean
metrics. The Log-Euclidean metric decreases tensor swelling, however, it is found to introduce other types of estimation biases. We find that for the case of
thermal MR noise (rician), the swelling effect reduces estimation bias, and conclude that the Euclidean metric is an appropriate selection.
1591. An Improved Method for Diffusional Kurtosis Estimation
Babak A. Ardekani 1,2 , Ali Tabesh, 1,3 , Jens H. Jensen 3 , Joseph A. Helpern, 1,3 , Alvin Bachman 1 , Howard
Kushner 4
1 Center for Advanced Brain Imaging, The Nathan S. Kline Institute for Psychiatric Research, Orangeburg, NY, United States;
2 Department of Psychiatry, New York University School of Medicine, New York, United States; 3 Department of Radiology, New
York University School of Medicine, New York, NY, United States; 4 Statistical Sciences and Research Division, The Nathan S. Kline
Institute for Psychiatric Research, Orangeburg, NY, United States
In diffusional kurtosis imaging (DKI), the non-Gaussian nature of water diffusion in biological tissue is characterized by a kurtosis parameter, estimated in
every voxel from a set of diffusion-weighted image acquisitions. This paper presents an improved method for estimating the kurtosis parameter in DKI. The
specific contributions of this paper are twofold. (1) We propose a new method for imposing a positive-definiteness constraint on the fourth order tensor
estimates and show its particular importance in DKI. (2) We propose using Mardia’s multivariate definition of kurtosis to characterize non-Gaussian
diffusion, as opposed to mean univariate kurtosis used in previous publications.
1592. Supertoroid-Based Fusion of Cardiac Dt-Mri with Molecular and Physiological Information
Choukri Mekkaoui 1,2 , Marcel Jackowski 3 , Roberto Martuzzi 1 , Albert Sinusas 1
1 Yale University School of Medicine, New Haven, CT, United States; 2 Harvard Medical School, Boston, MA, United States;
3 University of São Paulo
The supertoroid-based representation enhances the three-dimensional perception of biological tissue structure and organization using DT-MRI. The presence
of two additional free parameters in the supertoroidal function allows the tuning of the glyph surface in order to highlight different structural properties.
Alternatively, these parameters can be used to fuse the visualization of structure with complimentary information provided by other modalities. In this work,
we combined DT-MRI, MMP-targeted 99m Tc-labeled radiotracer (RP805) uptake, and 201 Tl perfusion on a porcine heart at 2-weeks post-MI, showing that the
supertoroidal model can fuse information arising from different modalities into a unique and comprehensive visualization scheme.