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Generalization of intravoxel incoherent motion model by introducing the notion of continuous pseudodiffusion variable
Author(s) -
Kuai ZiXiang,
Liu WanYu,
Zhang YanLi,
Zhu YueMin
Publication year - 2016
Publication title -
magnetic resonance in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.696
H-Index - 225
eISSN - 1522-2594
pISSN - 0740-3194
DOI - 10.1002/mrm.26064
Subject(s) - intravoxel incoherent motion , perfusion , mathematics , standard deviation , voxel , flow (mathematics) , diffusion , generalization , variable (mathematics) , nuclear medicine , nuclear magnetic resonance , magnetic resonance imaging , diffusion mri , mathematical analysis , physics , medicine , statistics , radiology , thermodynamics , geometry
Purpose A generalized intravoxel incoherent motion (IVIM) model, called the GIVIM, was proposed to better account for complex perfusion present in the tissues having various vessels and flow regimes, such as the liver. Theory and Methods The notions of continuous pseudodiffusion variable as well as perfusion fraction density function were introduced to describe the presence of multiple perfusion components in a voxel. The mean and standard deviation of Gaussian perfusion fraction density function were then used to define two new parameters, the mean pseudodiffusivity ( D ¯ ) and pseudodiffusion dispersion ( σ ). The GIVIM model was evaluated by testing whether or not it can reflect hepatic perfusion difference caused by flow‐compensated imaging sequences having different diffusion times. Also,D ¯was compared with D* in the standard IVIM model. Results The values of both D* andD ¯decreased after flow compensation and further decreased when shortening diffusion time.D ¯exhibited reduced variance in comparison with D* . In addition, σ also showed its sensitivity to hepatic perfusion difference caused by the flow‐compensated imaging sequences. Conclusion The GIVIM model has the ability to better describe multicomponent perfusion without lengthening acquisition time and knowing in advance the number and/or the variety of perfusion components. Magn Reson Med 76:1594–1603, 2016. © 2015 International Society for Magnetic Resonance in Medicine