Publications by authors named "Khieu Van Nguyen"

5 Publications

  • Page 1 of 1

SpinDoctor: A MATLAB toolbox for diffusion MRI simulation.

Neuroimage 2019 11 27;202:116120. Epub 2019 Aug 27.

INRIA Saclay, Equipe DEFI, CMAP, Ecole Polytechnique, Route de Saclay, 91128 Palaiseau Cedex, France.

The complex transverse water proton magnetization subject to diffusion-encoding magnetic field gradient pulses in a heterogeneous medium can be modeled by the multiple compartment Bloch-Torrey partial differential equation. Under the assumption of negligible water exchange between compartments, the time-dependent apparent diffusion coefficient can be directly computed from the solution of a diffusion equation subject to a time-dependent Neumann boundary condition. This paper describes a publicly available MATLAB toolbox called SpinDoctor that can be used 1) to solve the Bloch-Torrey partial differential equation in order to simulate the diffusion magnetic resonance imaging signal; 2) to solve a diffusion partial differential equation to obtain directly the apparent diffusion coefficient; 3) to compare the simulated apparent diffusion coefficient with a short-time approximation formula. The partial differential equations are solved by P1 finite elements combined with built-in MATLAB routines for solving ordinary differential equations. The finite element mesh generation is performed using an external package called Tetgen. SpinDoctor provides built-in options of including 1) spherical cells with a nucleus; 2) cylindrical cells with a myelin layer; 3) an extra-cellular space enclosed either a) in a box or b) in a tight wrapping around the cells; 4) deformation of canonical cells by bending and twisting; 5) permeable membranes; Built-in diffusion-encoding pulse sequences include the Pulsed Gradient Spin Echo and the Oscillating Gradient Spin Echo. We describe in detail how to use the SpinDoctor toolbox. We validate SpinDoctor simulations using reference signals computed by the Matrix Formalism method. We compare the accuracy and computational time of SpinDoctor simulations with Monte-Carlo simulations and show significant speed-up of SpinDoctor over Monte-Carlo simulations in complex geometries. We also illustrate several extensions of SpinDoctor functionalities, including the incorporation of T relaxation, the simulation of non-standard diffusion-encoding sequences, as well as the use of externally generated geometrical meshes.
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http://dx.doi.org/10.1016/j.neuroimage.2019.116120DOI Listing
November 2019

Efficient GPU-based Monte-Carlo simulation of diffusion in real astrocytes reconstructed from confocal microscopy.

J Magn Reson 2018 11 27;296:188-199. Epub 2018 Sep 27.

Molecular Imaging Research Center (MIRCen), Commissariat l'Energie Atomique, Fontenay-aux-Roses, France.

The primary goal of this work is to develop an efficient Monte-Carlo simulation of diffusion-weighted signal in complex cellular structures, such as astrocytes, directly derived from confocal microscopy. In this study, we first use an octree structure for spatial decomposition of surface meshes. Octree structure and radius-search algorithm help to quickly identify the faces that particles can possibly encounter during the next time step, thus speeding up the Monte-Carlo simulation. Furthermore, we propose to use a three-dimensional binary marker to describe the complex cellular structure and optimize the particle trajectory simulation. Finally, a GPU-based version of these two approaches is implemented for more efficient modeling. It is shown that the GPU-based binary marker approach yields unparalleled performance, opening up new possibilities to better understand intracellular diffusion, validate diffusion models, and create dictionaries of intracellular diffusion signatures.
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http://dx.doi.org/10.1016/j.jmr.2018.09.013DOI Listing
November 2018

Modulation of water diffusion by activation-induced neural cell swelling in Aplysia Californica.

Sci Rep 2017 07 21;7(1):6178. Epub 2017 Jul 21.

NeuroSpin, Bât 145, Joliot Institute, CEA-Paris-Saclay Center, Point Courrier 156, 91191, Gif-sur-Yvette, France.

Diffusion functional magnetic resonance imaging (DfMRI) has been proposed as a method for functional neuroimaging studies, as an alternative to blood oxygenation level dependent (BOLD)-fMRI. DfMRI is thought to more directly reflect neural activation, but its exact mechanism remains unclear. It has been hypothesized that the water apparent diffusion coefficient (ADC) decrease observed upon neural activation results from swelling of neurons or neuron parts. To elucidate the origin of the DfMRI response at cellular level we performed diffusion MR microscopy at 17.2 T in Aplysia californica buccal ganglia and compared the water ADCs at cellular and ganglia levels before and after neuronal activation induced by perfusion with a solution containing dopamine. Neural cell swelling, evidenced from optical microscopy imaging, resulted in an intracellular ADC increase and an ADC decrease at ganglia level. Furthermore, the intracellular ADC increase was found to have a significant positive correlation with the increase in cell size. Our results strongly support the hypothesis that the ADC decrease observed with DfMRI upon neuronal activation at tissue level reflects activation-induced neural cell swelling.
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http://dx.doi.org/10.1038/s41598-017-05586-5DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5522485PMC
July 2017

Quantitative DLA-based compressed sensing for T-weighted acquisitions.

J Magn Reson 2017 08 9;281:26-30. Epub 2017 May 9.

NeuroSpin, CEA Saclay, 91191 Gif-sur-Yvette, France; University Paris-Saclay, XI, 91450 Orsay, France. Electronic address:

High resolution Manganese Enhanced Magnetic Resonance Imaging (MEMRI), which uses manganese as a T contrast agent, has great potential for functional imaging of live neuronal tissue at single neuron scale. However, reaching high resolutions often requires long acquisition times which can lead to reduced image quality due to sample deterioration and hardware instability. Compressed Sensing (CS) techniques offer the opportunity to significantly reduce the imaging time. The purpose of this work is to test the feasibility of CS acquisitions based on Diffusion Limited Aggregation (DLA) sampling patterns for high resolution quantitative T-weighted imaging. Fully encoded and DLA-CS T-weighted images of Aplysia californica neural tissue were acquired on a 17.2T MRI system. The MR signal corresponding to single, identified neurons was quantified for both versions of the T weighted images. For a 50% undersampling, DLA-CS can accurately quantify signal intensities in T-weighted acquisitions leading to only 1.37% differences when compared to the fully encoded data, with minimal impact on image spatial resolution. In addition, we compared the conventional polynomial undersampling scheme with the DLA and showed that, for the data at hand, the latter performs better. Depending on the image signal to noise ratio, higher undersampling ratios can be used to further reduce the acquisition time in MEMRI based functional studies of living tissues.
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http://dx.doi.org/10.1016/j.jmr.2017.05.002DOI Listing
August 2017

DLA based compressed sensing for high resolution MR microscopy of neuronal tissue.

J Magn Reson 2015 Oct 31;259:186-91. Epub 2015 Aug 31.

Neurospin, CEA Saclay, 91191 Gif sur Yvette, France. Electronic address:

In this work we present the implementation of compressed sensing (CS) on a high field preclinical scanner (17.2 T) using an undersampling trajectory based on the diffusion limited aggregation (DLA) random growth model. When applied to a library of images this approach performs better than the traditional undersampling based on the polynomial probability density function. In addition, we show that the method is applicable to imaging live neuronal tissues, allowing significantly shorter acquisition times while maintaining the image quality necessary for identifying the majority of neurons via an automatic cell segmentation algorithm.
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http://dx.doi.org/10.1016/j.jmr.2015.08.012DOI Listing
October 2015