Search

Your search keyword '"Khieu Van Nguyen"' showing total 7 results
Start Over Author "Khieu Van Nguyen"
7 results on '"Khieu Van Nguyen"'

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

Author

Yoshifumi Abe, Khieu Van Nguyen, Tomokazu Tsurugizawa, Luisa Ciobanu, and Denis Le Bihan

Subjects
Medicine, Science
Abstract

Abstract 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.

Published
2017
Full Text
View/download PDF

2. The time-dependent diffusivity in the abdominal ganglion of Aplysia californica: experiments and simulations

Author

Khieu Van Nguyen, Denis Le Bihan, Jing-Rebecca Li, Luisa Ciobanu, Service NEUROSPIN (NEUROSPIN), Université Paris-Saclay-Direction de Recherche Fondamentale (CEA) (DRF (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA), Shape reconstruction and identification (DeFI ), Centre de Mathématiques Appliquées - Ecole Polytechnique (CMAP), École polytechnique (X)-Centre National de la Recherche Scientifique (CNRS)-École polytechnique (X)-Centre National de la Recherche Scientifique (CNRS)-Inria Saclay - Ile de France, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), ANR-13-BSV5-0014,ANImE,Mécanismes neuronaux d'un comportement complexe chez l'aplysie révélés conjointement par l'imagerie par résonance magnétique rehaussée au manganèse et l'électrophysiologie(2013), Direction de Recherche Fondamentale (CEA) (DRF (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay, Inria Saclay - Ile de France, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre de Mathématiques Appliquées - Ecole Polytechnique (CMAP), and École polytechnique (X)-Centre National de la Recherche Scientifique (CNRS)-École polytechnique (X)-Centre National de la Recherche Scientifique (CNRS)

Subjects
Materials science, biology, [SDV.IB.IMA]Life Sciences [q-bio]/Bioengineering/Imaging, Thermal diffusivity, biology.organism_classification, [INFO.INFO-MO]Computer Science [cs]/Modeling and Simulation, 030218 nuclear medicine & medical imaging, Diffusion MRI, 03 medical and health sciences, 0302 clinical medicine, ADC, Abdominal ganglion, Aplysia, Biophysics, 030217 neurology & neurosurgery, General Nursing, Simulation
Abstract

International audience; The nerve cells of theAplysiaare much larger than mammalian neurons. Using theAplysiaganglia tostudy the relationship between the cellular structure and the diffusion MRI signal can potentially shedlight on this relationship for more complex organisms. We measured the dMRI signal of chemically-fixed abdominal ganglia of theAplysiaat several diffusion times. At the diffusion times measured andobserved at low b-values, the dMRI signal is mono-exponential and can be accurately represented bythe parameter ADC(Apparent Diffusion Coefficient). We performed numerical simulations of waterdiffusion for the large cell neurons in the abdominal ganglia after creating geometrical configurationsby segmenting high resolution T2-weighted(T2w)images to obtain the cell outline and thenincorporating a manually generated nucleus. The results of the numerical simulations validate theclaim that water diffusion in the large cell neurons is in the short diffusion time regime at ourexperimental diffusion times. Then, using the analytical short time approximation(STA)formula forthe ADC, we showed that in order to explain the experimentally observed behavior, it is necessary toconsider the nucleus and the cytoplasm as two separate diffusion compartments. By using a twocompartment STA model, we were able to illustrate the effect of the highly irregular shape of the cell nucleus on the ADC.

Published
2019

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

Author

Julien Valette, Khieu Van Nguyen, Edwin Hernández-Garzón, Laboratoire des Maladies Neurodégénératives - UMR 9199 (LMN), Centre National de la Recherche Scientifique (CNRS)-Service MIRCEN (MIRCEN), Université Paris-Saclay-Institut de Biologie François JACOB (JACOB), Direction de Recherche Fondamentale (CEA) (DRF (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Direction de Recherche Fondamentale (CEA) (DRF (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay-Institut de Biologie François JACOB (JACOB), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA), European Project: 336331,EC:FP7:ERC,ERC-2013-StG,INCELL(2013), Service MIRCEN (MIRCEN), Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Institut de Biologie François JACOB (JACOB), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Institut de Biologie François JACOB (JACOB), and Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Centre National de la Recherche Scientifique (CNRS)

Subjects
Nuclear and High Energy Physics, Computer science, [SDV.IB.IMA]Life Sciences [q-bio]/Bioengineering/Imaging, Monte Carlo method, Biophysics, Binary number, Time step, Condensed Matter Physics, Biochemistry, Signal, 030218 nuclear medicine & medical imaging, Computational science, law.invention, 03 medical and health sciences, Octree, 0302 clinical medicine, Confocal microscopy, law, Polygon mesh, Diffusion (business), 030217 neurology & neurosurgery
Abstract

International audience; 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 mod-eling. 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.

Published
2018

4. Quantitative DLA-based compressed sensing for T

Author

Pavel, Svehla, Khieu-Van, Nguyen, Jing-Rebecca, Li, and Luisa, Ciobanu

Abstract

High resolution Manganese Enhanced Magnetic Resonance Imaging (MEMRI), which uses manganese as a T

Published
2017

5. Quantitative DLA-based compressed sensing for T1-weighted acquisitions

Author

Jing-Rebecca Li, Luisa Ciobanu, Pavel Svehla, Khieu Van Nguyen, Service NEUROSPIN (NEUROSPIN), Direction de Recherche Fondamentale (CEA) (DRF (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay, Université Paris-Sud - Paris 11 (UP11), Shape reconstruction and identification (DeFI ), Inria Saclay - Ile de France, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre de Mathématiques Appliquées - Ecole Polytechnique (CMAP), École polytechnique (X)-Centre National de la Recherche Scientifique (CNRS)-École polytechnique (X)-Centre National de la Recherche Scientifique (CNRS), Université Paris-Saclay-Direction de Recherche Fondamentale (CEA) (DRF (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA), Centre de Mathématiques Appliquées - Ecole Polytechnique (CMAP), École polytechnique (X)-Centre National de la Recherche Scientifique (CNRS)-École polytechnique (X)-Centre National de la Recherche Scientifique (CNRS)-Inria Saclay - Ile de France, and Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)

Subjects
Nuclear and High Energy Physics, Image quality, Computer science, [SDV.IB.IMA]Life Sciences [q-bio]/Bioengineering/Imaging, Biophysics, Biochemistry, Signal, 030218 nuclear medicine & medical imaging, 03 medical and health sciences, 0302 clinical medicine, Nuclear magnetic resonance, Sampling (signal processing), medicine, Image resolution, ComputingMilieux_MISCELLANEOUS, medicine.diagnostic_test, business.industry, Noise (signal processing), Magnetic resonance imaging, Pattern recognition, Condensed Matter Physics, [INFO.INFO-MO]Computer Science [cs]/Modeling and Simulation, Compressed sensing, Undersampling, Artificial intelligence, business, 030217 neurology & neurosurgery
Abstract

High resolution Manganese Enhanced Magnetic Resonance Imaging (MEMRI), which uses manganese as a T1 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 T1-weighted imaging. Fully encoded and DLA-CS T1-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 T1 weighted images. For a 50% undersampling, DLA-CS can accurately quantify signal intensities in T1-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.

Published
2017

6. SpinDoctor: A MATLAB toolbox for diffusion MRI simulation

Author

Van Dang Nguyen, Hoang Trong An Tran, Thi Minh Phuong Nguyen, Try Nguyen Tran, Duc Thach Son Vu, Hoang An Tran, Jan Valdman, Cong-Bang Trang, Khieu Van Nguyen, Jing-Rebecca Li, Shape reconstruction and identification (DeFI ), Inria Saclay - Ile de France, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre de Mathématiques Appliquées - Ecole Polytechnique (CMAP), École polytechnique (X)-Centre National de la Recherche Scientifique (CNRS)-École polytechnique (X)-Centre National de la Recherche Scientifique (CNRS), Division of Computational Science and Technology [Stockholm] (CST), Royal Institute of Technology [Stockholm] (KTH ), University of South Bohemia, Jan Valdman was supportedby the Czech Science Foundation (GACR), through the grant GA17-04301S. Van-Dang Nguyenwas supported by the Swedish Energy Agency, Sweden with the project ID P40435-1 and MSO4SCwith the grant number 731063., Centre de Mathématiques Appliquées - Ecole Polytechnique (CMAP), École polytechnique (X)-Centre National de la Recherche Scientifique (CNRS)-École polytechnique (X)-Centre National de la Recherche Scientifique (CNRS)-Inria Saclay - Ile de France, and Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)

Subjects
Diffusion equation, Diffusion magnetic resonance imaging, [SDV.IB.IMA]Life Sciences [q-bio]/Bioengineering/Imaging, Cognitive Neuroscience, Finite elements, FOS: Physical sciences, Neuroimaging, 050105 experimental psychology, 03 medical and health sciences, 0302 clinical medicine, FOS: Mathematics, Neumann boundary condition, Humans, Effective diffusion coefficient, Computer Simulation, 0501 psychology and cognitive sciences, Mathematics - Numerical Analysis, Diffusion (business), Partial differential equation, Bloch-Torrey equation, 05 social sciences, Mathematical analysis, Brain, Numerical Analysis (math.NA), Models, Theoretical, Computational Physics (physics.comp-ph), [INFO.INFO-MO]Computer Science [cs]/Modeling and Simulation, Finite element method, Apparent diffusion coefficient, Neurology, Ordinary differential equation, Spin echo, Physics - Computational Physics, Software, Simulation, 030217 neurology & neurosurgery
Abstract

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 (BTPDE). A mathematical model for the time-dependent apparent diffusion coefficient (ADC), called the H-ADC model, was obtained recently using homogenization techniques on the BTPDE. Under the assumption of negligible water exchange between compartments, the H-ADC model produces the ADC of a diffusion medium from the solution of a diffusion equation (DE) 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 BTPDE to obtain the dMRI signal (the toolbox provides a way of robustly fitting the dMRI signal to obtain the fitted ADC); 2) to solve the DE of the H-ADC model to obtain the ADC; 3) a short-time approximation formula for the ADC is also included in the toolbox for comparison with the simulated ADC. The PDEs are solved by P 1 finite elements combined with build-in Matlab routines for solving ordinary differential equations. The finite element mesh generation is performed using an external package called Tetgen that is included in the toolbox. 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 (ECS) 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 for the BT-PDE (the H-ADC assumes negligible permeability). Built-in diffusion-encoding pulse sequences include the Pulsed Gradient Spin Echo and the Oscilating Gradient Spin Echo., 49 pages, 18 figures

Published
2019

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

Author

Luisa Ciobanu, Guillaume Radecki, Khieu Van Nguyen, Jing-Rebecca Li, Service NEUROSPIN (NEUROSPIN), Direction de Recherche Fondamentale (CEA) (DRF (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay, Université Paris-Sud - Paris 11 (UP11), Shape reconstruction and identification (DeFI ), Inria Saclay - Ile de France, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre de Mathématiques Appliquées - Ecole Polytechnique (CMAP), École polytechnique (X)-Centre National de la Recherche Scientifique (CNRS)-École polytechnique (X)-Centre National de la Recherche Scientifique (CNRS), INRIA Saclay Equipe DEFI and CEA Neurospin, Université Paris-Saclay-Direction de Recherche Fondamentale (CEA) (DRF (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA), Centre de Mathématiques Appliquées - Ecole Polytechnique (CMAP), École polytechnique (X)-Centre National de la Recherche Scientifique (CNRS)-École polytechnique (X)-Centre National de la Recherche Scientifique (CNRS)-Inria Saclay - Ile de France, and Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)

Subjects
Nuclear and High Energy Physics, Scanner, Polynomial, Magnetic Resonance Spectroscopy, Image quality, Computer science, [SDV.IB.IMA]Life Sciences [q-bio]/Bioengineering/Imaging, Biophysics, Probability density function, Biochemistry, 030218 nuclear medicine & medical imaging, Diffusion, 03 medical and health sciences, 0302 clinical medicine, Nuclear magnetic resonance, Aplysia, Microscopy, Diffusion-limited aggregation, Image Processing, Computer-Assisted, Animals, Nerve Tissue, ComputingMilieux_MISCELLANEOUS, Neurons, Phantoms, Imaging, business.industry, Pattern recognition, Image Enhancement, Condensed Matter Physics, Magnetic Resonance Imaging, Ganglia, Invertebrate, Compressed sensing, Undersampling, Artificial intelligence, business, Algorithms, 030217 neurology & neurosurgery
Abstract

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.

Published
2015

Catalog

Books, media, physical & digital resources
See catalog results