Rapid measurement of intravoxel incoherent motion (IVIM) derived perfusion fraction for clinical magnetic resonance imaging

MAGMA. 2018 Apr;31(2):269-283. doi: 10.1007/s10334-017-0656-6. Epub 2017 Oct 26.

Abstract

Objective: This study aimed to investigate the reliability of intravoxel incoherent motion (IVIM) model derived parameters D and f and their dependence on b value distributions with a rapid three b value acquisition protocol.

Materials and methods: Diffusion models for brain, kidney, and liver were assessed for bias, error, and reproducibility for the estimated IVIM parameters using b values 0 and 1000, and a b value between 200 and 900, at signal-to-noise ratios (SNR) 40, 55, and 80. Relative errors were used to estimate optimal b value distributions for each tissue scenario. Sixteen volunteers underwent brain DW-MRI, for which bias and coefficient of variation were determined in the grey matter.

Results: Bias had a large influence in the estimation of D and f for the low-perfused brain model, particularly at lower b values, with the same trends being confirmed by in vivo imaging. Significant differences were demonstrated in vivo for estimation of D (P = 0.029) and f (P < 0.001) with [300,1000] and [500,1000] distributions. The effect of bias was considerably lower for the high-perfused models. The optimal b value distributions were estimated to be brain500,1000, kidney300,1000, and liver200,1000.

Conclusion: IVIM parameters can be estimated using a rapid DW-MRI protocol, where the optimal b value distribution depends on tissue characteristics and compromise between bias and variability.

Keywords: Biological models; Diffusion weighted magnetic resonance imaging (DW-MRI); Intravoxel incoherent motion (IVIM); Perfusion.

MeSH terms

  • Adult
  • Algorithms
  • Brain / diagnostic imaging
  • Cohort Studies
  • Computer Simulation
  • Diffusion Magnetic Resonance Imaging*
  • Humans
  • Image Interpretation, Computer-Assisted / methods
  • Kidney / diagnostic imaging
  • Liver / diagnostic imaging
  • Models, Statistical
  • Motion
  • Perfusion
  • Reproducibility of Results
  • Signal-To-Noise Ratio