Diffusion Microscopist Simulator: A General Monte Carlo Simulation System for Diffusion Magnetic Resonance Imaging

被引:29
作者
Yeh, Chun-Hung [1 ,2 ,3 ]
Schmitt, Benoit [2 ,3 ]
Le Bihan, Denis [2 ,3 ]
Li-Schlittgen, Jing-Rebecca [4 ]
Lin, Ching-Po [1 ]
Poupon, Cyril [2 ,3 ]
机构
[1] Natl Yang Ming Univ, Inst Neurosci, Taipei 112, Taiwan
[2] Commissariat Energie Atom & Energies Alternat CEA, NeuroSpin, Gif Sur Yvette, France
[3] Inst Federatif Rech 49, Gif Sur Yvette, France
[4] Inst Natl Rech Informat & Automat INRIA Saclay, Determinat Formes & Identificat Equipe DEFI, Palaiseau, France
关键词
RELAXATION-TIME NMR; BRAIN WHITE-MATTER; HIGH B-VALUE; SPIN-ECHO; SELF-DIFFUSION; WATER DIFFUSION; FIBER-TRACKING; FIELD-GRADIENT; MULTICOMPARTMENT SYSTEMS; RESTRICTED DIFFUSION;
D O I
10.1371/journal.pone.0076626
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
This article describes the development and application of an integrated, generalized, and efficient Monte Carlo simulation system for diffusion magnetic resonance imaging (dMRI), named Diffusion Microscopist Simulator (DMS). DMS comprises a random walk Monte Carlo simulator and an MR image synthesizer. The former has the capacity to perform large-scale simulations of Brownian dynamics in the virtual environments of neural tissues at various levels of complexity, and the latter is flexible enough to synthesize dMRI datasets from a variety of simulated MRI pulse sequences. The aims of DMS are to give insights into the link between the fundamental diffusion process in biological tissues and the features observed in dMRI, as well as to provide appropriate ground-truth information for the development, optimization, and validation of dMRI acquisition schemes for different applications. The validity, efficiency, and potential applications of DMS are evaluated through four benchmark experiments, including the simulated dMRI of white matter fibers, the multiple scattering diffusion imaging, the biophysical modeling of polar cell membranes, and the high angular resolution diffusion imaging and fiber tractography of complex fiber configurations. We expect that this novel software tool would be substantially advantageous to clarify the interrelationship between dMRI and the microscopic characteristics of brain tissues, and to advance the biophysical modeling and the dMRI methodologies.
引用
收藏
页数:12
相关论文
共 80 条
[31]  
HAZLEWOOD CF, 1991, MAGNET RESON MED, V19, P214
[32]   Q-ball reconstruction of multimodal fiber orientations using the spherical harmonic basis [J].
Hess, Christopher P. ;
Mukherjee, Pratik ;
Han, Eric T. ;
Xu, Duan ;
Vigneron, Daniel B. .
MAGNETIC RESONANCE IN MEDICINE, 2006, 56 (01) :104-117
[33]  
Jones DK, 1999, MAGN RESON MED, V42, P37, DOI 10.1002/(SICI)1522-2594(199907)42:1<37::AID-MRM7>3.0.CO
[34]  
2-O
[35]  
Jones DK, 1999, MAGNET RESON MED, V42, P515, DOI 10.1002/(SICI)1522-2594(199909)42:3<515::AID-MRM14>3.0.CO
[36]  
2-Q
[37]  
Karger J., 1988, Adv. Magn. Reson, V12, P1
[38]   MODIFIED PULSED GRADIENT TECHNIQUE FOR MEASURING DIFFUSION IN THE PRESENCE OF LARGE BACKGROUND GRADIENTS [J].
KARLICEK, RF ;
LOWE, IJ .
JOURNAL OF MAGNETIC RESONANCE, 1980, 37 (01) :75-91
[39]   Use of magnetic resonance to measure molecular diffusion within the brain extracellular space [J].
Kroenke, CD ;
Neil, JJ .
NEUROCHEMISTRY INTERNATIONAL, 2004, 45 (04) :561-568
[40]   Complex geometric models of diffusion and relaxation in healthy and damaged white matter [J].
Landman, Bennett A. ;
Farrell, Jonathan A. D. ;
Smith, Seth A. ;
Reich, Daniel S. ;
Calabresi, Peter A. ;
van Zijl, Peter C. M. .
NMR IN BIOMEDICINE, 2010, 23 (02) :152-162