Generalization of intravoxel incoherent motion model by introducing the notion of continuous pseudodiffusion variable

Kuai, Zi‐Xiang; Liu, Wan-Yu; Zhang, Yanli; Zhu, Yuemin

doi:10.1002/mrm.26064

Cited by 16 publications

(22 citation statements)

References 40 publications

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“…Further, the exact nature of the IVIM signal is not well understood and is a hot current research topic. For example, flow-compensated diffusion gradients, [132][133][134][135][136] extension of the current model, 38,137 and anisotropy studies [138][139][140] have been used to gain insight into the nature of the IVIM perfusion signal. Importantly, an already relatively large number of clinical studies have shown promising results for application in disease diagnosis, follow-up, and prognosis.…”

Section: Discussionmentioning

confidence: 99%

Intravoxel incoherent motion MRI as a means to measure in vivo perfusion: A review of the evidence

Federau

2017

NMR in Biomedicine

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The idea that in vivo intravoxel incoherent motion magnetic resonance signal is influenced by blood motion in the microvasculature is exciting, because it suggests that local and quantitative perfusion information can be obtained in a simple and elegant way from a few diffusion-weighted images, without contrast injection. When the method was proposed in the late 1980s some doubts appeared as to its feasibility, and, probably because the signal to noise and image quality at the time was not sufficient, no obvious experimental evidence could be produced to alleviate them. Helped by the tremendous improvements seen in the last three decades in MR hardware, pulse design, and post-processing capabilities, an increasing number of encouraging reports on the value of intravoxel incoherent motion perfusion imaging have emerged. The aim of this article is to review the current published evidence on the feasibility of in vivo perfusion imaging with intravoxel incoherent motion MRI.

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Section: Discussionmentioning

confidence: 99%

Intravoxel incoherent motion MRI as a means to measure in vivo perfusion: A review of the evidence

Federau

2017

NMR in Biomedicine

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“…16,19 4 | RESULTS Figure 2 depicts one volunteer's normalized BP70 DW signal value at each b-value and the signal fitting curves derived from the GIVIM, the GIVIM-GMM and the triexponential model. In order to overcome the excessive dependence on initial value and the premature local extremum and to accelerate the LM algorithm, particle swarm optimization (PSO) was introduced.…”

Section: Fitting Methodsmentioning

confidence: 99%

“…19 like the estimation of the distribution function. 19 like the estimation of the distribution function.…”

Section: F I G U R Ementioning

confidence: 99%

“…In 1994, a hierarchical model with several perfusion components was proposed based on a simple vascular network. 19,20 In this model, the pseudodiffusion variable is continuous; the number of perfusion components is infinite and the perfusion fraction density obeys the Normal distribution. To deal with these problems, some other multiexponential IVIM models, such as the triexponential IVIM model 16 and the five-compartmental microcirculatory model, 17 were proposed by adding a number of perfusion components.…”

Section: Introductionmentioning

confidence: 99%

“…In order to overcome this difficulty, a generalized IVIM model (GIVIM) was introduced. 19,20 In this model, the pseudodiffusion variable is continuous; the number of perfusion components is infinite and the perfusion fraction density obeys the Normal distribution. However, different organs have more or less complex vascular systems and the vascular distribution in organs is regional.…”

Section: Introductionmentioning

confidence: 99%

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Depiction of the perfusion components’ volume fraction distribution in generalized intravoxel incoherent motion by using Gaussian mixture model

Wang

Liu

Kuai

et al. 2018

Concepts Magn Reson

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Gaussian mixture model (GMM) was proposed to depict the perfusion volume fraction distribution in the generalized intravoxel incoherent motion model (GIVIM) to improve GIVIM's ability of describing complex perfusion conditions and their changes. Different hepatic perfusion conditions were accounted for by performing different combinations of imaging sequence and diffusion time on six normal livers. In order to evaluate GIVIM-GMM's reliability in perfusion condition analysis, the fitting to diffusion-weighted (DW) data and the consistency between diffusion-related parameters' change and the data's change were tested and the recent GIVIM and the triexponential models were chosen for comparison.The difference of the fitting results was evaluated by performing the extra-sum-ofsquares F test and information criteria on normal human DW data. The difference of the consistency was assessed by using two-tailed paired Student's t test. In the extra-sum-of-squares F test, the relative difference ratio F values derived from the GIVIM and GIVIM-GMM and that derived from the triexponential model and the GIVIM-GMM are respectively 25.334 and 27.976, which indicates that significant difference existed and that the GIVIM-GMM provides better fit to the normal human liver DW data. In information criteria test, the evidence ratio values were determined by dividing the GIVIM's or triexponential model's correct probability by the GIVIM-GMM's. Both evidence ratio values (2.3942 × 10 −10 , 8.6167 × 10 −9 , respectively) are much smaller than 1, which also expresses that the best model used to fit the normal human liver DW data was the GIVIM-GMM. In two-tailed paired student's t test, the GIVIM-GMM provides more parameters to give a finer description of perfusion than the triexponential model or GIVIM. In short, all the results demonstrated that the GIVIM-GMM provides better performance than the existing IVIM models for depicting the signal attenuation in DW imaging. K E Y W O R D Scontinuous pseudodiffusion variable, diffusion-weighted imaging, flow compensation, Gaussian mixture model, Intravoxel incoherent motion, liver

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Initial experience of generalized intravoxel incoherent motion imaging and diffusion tensor imaging (GIVIM‐DTI) in healthy subjects

Chen

Zhao

et al. 2016

Magnetic Resonance Imaging

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Generalization of intravoxel incoherent motion model by introducing the notion of continuous pseudodiffusion variable

Cited by 16 publications

References 40 publications

Intravoxel incoherent motion MRI as a means to measure in vivo perfusion: A review of the evidence

Intravoxel incoherent motion MRI as a means to measure in vivo perfusion: A review of the evidence

Depiction of the perfusion components’ volume fraction distribution in generalized intravoxel incoherent motion by using Gaussian mixture model

Initial experience of generalized intravoxel incoherent motion imaging and diffusion tensor imaging (GIVIM‐DTI) in healthy subjects

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