Numerical study of a macroscopic finite pulse model of the diffusion MRI signal

被引:20
作者
Li, Jing-Rebecca [1 ]
Hang Tuan Nguyen [2 ]
Dang Van Nguyen [1 ]
Haddar, Houssem [1 ]
Coatleven, Julien [1 ]
Le Bihan, Denis [2 ]
机构
[1] Ecole Polytech, INRIA Saclay Equipe DEFI CMAP, F-91128 Palaiseau, France
[2] CEA Saclay Ctr, NeuroSpin, F-91191 Gif Sur Yvette, France
关键词
Diffusion MRI; Signal model; Homogenization; Effective medium; Macroscopic model; Karger model; DUAL-POROSITY SYSTEMS; WATER DIFFUSION; WHITE-MATTER; HUMAN BRAIN; GRAVITATIONAL FORCES; RESTRICTED DIFFUSION; FIELD GRADIENT; OPTIC-NERVE; EXCHANGE; NMR;
D O I
10.1016/j.jmr.2014.09.004
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
Diffusion magnetic resonance imaging (dMRI) is an imaging modality that probes the diffusion characteristics of a sample via the application of magnetic field gradient pulses. The dMRI signal from a heterogeneous sample includes the contribution of the water proton magnetization from all spatial positions in a voxel. If the voxel can be spatially divided into different Gaussian diffusion compartments with inter-compartment exchange governed by linear kinetics, then the dMRI signal can be approximated using the macroscopic Karger model, which is a system of coupled ordinary differential equations (ODES), under the assumption that the duration of the diffusion-encoding gradient pulses is short compared to the diffusion time (the narrow pulse assumption). Recently, a new macroscopic model of the dMRI signal, without the narrow pulse restriction, was derived from the Bloch-Torrey partial differential equation (PDE) using periodic homogenization techniques. When restricted to narrow pulses, this new homogenized model has the same form as the Karger model. We conduct a numerical study of the new homogenized model for voxels that are made up of periodic copies of a representative volume that contains spherical and cylindrical cells of various sizes and orientations and show that the signal predicted by the new model approaches the reference signal obtained by solving the full Bloch-Torrey PDE in 0(82), where a is the ratio between the size of the representative volume and a measure of the diffusion length. When the narrow gradient pulse assumption is not satisfied, the new homogenized model offers a much better approximation of the full PDE signal than the Karger model. Finally, preliminary results of applying the new model to a voxel that is not made up of periodic copies of a representative volume are shown and discussed. (C) 2014 Elsevier Inc. All rights reserved.
引用
收藏
页码:54 / 65
页数:12
相关论文
共 50 条
  • [21] A diffusion MRI model for random walks confined on cylindrical surfaces: towards non-invasive quantification of myelin sheath radius
    Canales-Rodriguez, Erick J.
    Tax, Chantal M. W.
    Fischi-Gomez, Elda
    Jones, Derek K.
    Thiran, Jean-Philippe
    Rafael-Patino, Jonathan
    FRONTIERS IN PHYSICS, 2025, 13
  • [22] In vivo mapping of macroscopic neuronal projections in the mouse hippocampus using high-resolution diffusion MRI
    Wu, Dan
    Zhang, Jiangyang
    NEUROIMAGE, 2016, 125 : 84 - 93
  • [23] MULTI TISSUE MODELLING OF DIFFUSION MRI SIGNAL REVEALS VOLUME FRACTION BIAS
    Frigo, Matteo
    Fick, Rutger H. J.
    Zucchelli, Mauro
    Deslauriers-Gauthier, Samuel
    Deriche, Rachid
    2020 IEEE 17TH INTERNATIONAL SYMPOSIUM ON BIOMEDICAL IMAGING (ISBI 2020), 2020, : 991 - 994
  • [24] Practical computation of the diffusion MRI signal of realistic neurons based on Laplace eigenfunctions
    Li, Jing-Rebecca
    Try Nguyen Tran
    Van-Dang Nguyen
    NMR IN BIOMEDICINE, 2020, 33 (10)
  • [25] Relationship between the Diffusion Time and the Diffusion MRI Signal Observed at 17.2 Tesla in the Healthy Rat Brain Cortex
    Pyatigorskaya, Nadya
    Le Bihan, Denis
    Reynaud, Olivier
    Ciobanu, Luisa
    MAGNETIC RESONANCE IN MEDICINE, 2014, 72 (02) : 492 - 500
  • [26] PGSE, OGSE, and Sensitivity to Axon Diameter in Diffusion MRI: Insight from a Simulation Study
    Drobnjak, Ivana
    Zhang, Hui
    Ianus, Andrada
    Kaden, Enrico
    Alexander, Daniel C.
    MAGNETIC RESONANCE IN MEDICINE, 2016, 75 (02) : 688 - 700
  • [27] ANALYSIS OF ADC MODEL ROBUSTNESS IN DIFFUSION-WEIGHTED MRI
    Taqdees, Syeda Warda
    Ng, Amanda
    Wright, David K.
    Tolcos, Mary
    Johnston, Leigh A.
    2017 IEEE 14TH INTERNATIONAL SYMPOSIUM ON BIOMEDICAL IMAGING (ISBI 2017), 2017, : 966 - 969
  • [28] Diffusion MRI signal reconstruction with continuity constraint and optimal regularization
    Caruyer, Emmanuel
    Deriche, Rachid
    MEDICAL IMAGE ANALYSIS, 2012, 16 (06) : 1113 - 1120
  • [29] Estimating non-gaussian diffusion model parameters in the presence of physiological noise and rician signal bias
    Kristoffersen, Anders
    JOURNAL OF MAGNETIC RESONANCE IMAGING, 2012, 35 (01) : 181 - 189
  • [30] Effects of Diffusion MRI Model and Harmonization on the Consistency of Findings in an International Multi-cohort HIV Neuroimaging Study
    Nir, Talia M.
    Lam, Hei Y.
    Ananworanich, Jintanat
    Boban, Jasmina
    Brew, Bruce J.
    Cysique, Lucette
    Fouche, J. P.
    Kuhn, Taylor
    Porges, Eric S.
    Law, Meng
    Paul, Robert H.
    Thames, April
    Woods, Adam J.
    Valcour, Victor G.
    Thompson, Paul M.
    Cohen, Ronald A.
    Stein, Dan J.
    Jahanshad, Neda
    COMPUTATIONAL DIFFUSION MRI (CDMRI 2018), 2019, : 203 - 215