Estimation of intravoxel incoherent motion parameters using low b-values.

Chen Ye,Zixiang Kuai,Yongbin Qin,Daoyun Xu,Wuchao Li,Yuemin Zhu,Lihui Wang,Rongpin Wang

doi:10.1371/journal.pone.0211911

Abstract

Intravoxel incoherent motion (IVIM) imaging is a magnetic resonance imaging (MRI) technique widely used in clinical applications for various organs. However, IVIM imaging at low b-values is a persistent problem. This paper aims to investigate in a systematic and detailed manner how the number of low b-values influences the estimation of IVIM parameters. To this end, diffusion-weighted (DW) data with different low b-values were simulated to get insight into the distributions of subsequent IVIM parameters. Then, in vivo DW data with different numbers of low b-values and different number of excitations (NEX) were acquired. Finally, least-squares (LSQ) and Bayesian shrinkage prior (BSP) fitting methods were implemented to estimate IVIM parameters. The influence of the number of low b-values on IVIM parameters was analyzed in terms of relative error (RE) and structural similarity (SSIM). The results showed that the influence of the number of low b-values on IVIM parameters is variable. LSQ is more dependent on the number of low b-values than BSP, but the latter is more sensitive to noise.

Highlights

Intravoxel incoherent motion (IVIM) imaging is a magnetic resonance imaging (MRI) technique widely used in clinical applications for various organs
To compare quantitatively the joint effects of low b-value, signal-to-noise ratio (SNR) and fitting method on the estimation of IVIM parameters, several simulations were performed with different combinations
Concerning the influence of SNR, our results suggest that the estimation accuracy of Bayesian shrinkage prior (BSP) for D is more sensitive to noise; the fewer the number of low b-values, the more obvious the effect

Summary

Introduction

Intravoxel incoherent motion (IVIM) imaging is a magnetic resonance imaging (MRI) technique widely used in clinical applications for various organs. It consists in extracting perfusion information from diffusion-weighted (DW) signals [1,2,3]. In this technique, the attenuation of DW signals at each image voxel is assumed to be caused by both the diffusion of water molecules in tissues and the microcirculation of blood inside blood vessels, which is called intravascular perfusion or pseudo-diffusion. Pseudo-diffusion parameter has much higher value than diffusion parameter. When the b-value is higher (saying higher than 200 s/mm2), diffusion plays a dominant role

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