Traditional Posters: Diffusion & Perfusion - ismrm

models, this methodology provides diffusion metrics that are more stable, and therefore more sensitive to a wider range of treatment
effects.
1584. DWI Signal from a Medium with Heterogeneous Diffusivity
Dmitry S. Novikov 1 , Valerij G. Kiselev 2
1 Radiology, NYU School of Medicine, New York, NY, United States; 2 Medical Physics, Diagnostic Radiology,
Uniklinikum Freiburg, Freiburg, Germany
We consider the DWI signal from any medium (tissue) in which the diffusion coefficient varies in space. Using recently developed
effective-medium approach, we relate the signal to the diffusivity correlation function. Explicit formulas for time-dependent diffusion
coefficient and diffusional kurtosis are provided in the case when the local diffusivity varies on a well-defined length scale. Our
results are numerically confirmed by the Monte-Carlo simulation of diffusion in a two-dimensional model tissue. While the DWI
signal has an approximately biexponential form, it is shown to be qualitatively different from that of the two-compartment exchange
(Kärger) model.
1585. From Single- To Double-PFG: Gleaning New Microstructural Information in
Complex Specimens
Noam Shemesh 1 , Evren Özarslan 2 , Peter J. Basser 2 , Yoram Cohen 1
1 School of Chemistry, Tel Aviv University, Tel Aviv, Israel; 2 Section on Tissue Biophysics and Biomimetics,
NICHD, National Institutes of Health, Bethesda, MD, United States
Although single-pulsed-field-gradient (s-PFG) methodologies such as DTI and the q-space approach are widely used to probe tissue
microstructures, they suffer from inherent limitations, especially when specimens are characterized by randomly oriented
compartments or size distributions. The double-PFG (d-PFG) is emerging as a new probe for novel microstructural information that
cannot be achieved by other means. Here we demonstrate that d-PFG can be used to extract accurate compartment dimensions at low
q-values both in phantoms and in biological cells which are randomly oriented, and in optic and sciatic nerves. The d-PFG may
become an important MRI method in the CNS.
1586. New Quantitative Indices for DWI of the Brain Tissue at High B-Values
Farida Grinberg 1 , Ezequiel A. Farrher 1 , Joachim Kaffanke 1 , Ana-Maria Oros-
Peusquens 1 , N. Jon Jon Shah 1,2
1 Medical Imaging Physics, Institute of Neuroscience and Medicine 4, Forschungszentrum Juelich GmbH,
Juelich, Germany; 2 Department of Neurology, Faculty of Medicine, RWTH Aachen University, Aachen,
Germany
Diffusion MRI permits non-invasive probing of tissue microstructure and function and provides invaluable information in brain
diagnostics. Conventional methods, however, are designed to retrieve only the average diffusion characteristics and tend to ignore
deviations from simple Gaussian behaviour. Recently, increasing efforts have been dedicated to the development of the advanced
approaches capable of capturing more detailed information on the propagation mechanisms. In this work, we report an in vivo
diffusion study of the brain based on a detailed analysis of the attenuation patterns. New quantitative indices are suggested as map
parameters and their potential use with respect to studies of the brain is discussed.
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 nonparametric
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.