Diffusion kurtosis imaging of the human kidney: a feasibility study

Magn Reson Imaging. 2014 Jun;32(5):413-20. doi: 10.1016/j.mri.2014.01.006. Epub 2014 Jan 28.

Abstract

Purpose: To assess the feasibility and to optimize imaging parameters of diffusion kurtosis imaging (DKI) in human kidneys.

Methods: The kidneys of ten healthy volunteers were examined on a clinical 3T MR scanner. For DKI, respiratory triggered EPI sequences were acquired in the coronal plane (3 b-values: 0, 300, 600s/mm(2), 30 diffusion directions). A goodness of fit analysis was performed and the influence of the signal-to-noise ratio (SNR) on the DKI results was evaluated. Region-of-interest (ROI) measurements were performed to determine apparent diffusion coefficient (ADC), fractional anisotropy (FA) and mean kurtosis (MK) of the cortex and the medulla of the kidneys. Intra-observer and inter-observer reproducibility using Bland-Altman plots as well as subjective image quality of DKI were examined and ADC, FA, and MK parameters were compared.

Results: The DKI model fitted better to the experimental data (r=0.99) with p<0.05 than the common mono-exponential ADC model (r=0.96). Calculation of reliable kurtosis parameters in human kidneys requires a minimum SNR of 8.31 on b=0s/mm(2) images. Corticomedullary differentiation was possible on FA and MK maps. ADC, FA and MK revealed significant differences in medulla (ADC=2.82 × 10(-3)mm(2)/s±0.25, FA=0.42±0. 05, MK=0.78±0.07) and cortex (ADC=3.60 × 10(-3)mm(2)/s±0.28, FA=0.18±0.04, MK=0.94±0.07) with p<0.001.

Conclusion: Our initial results indicate the feasibility of DKI in the human kidney presuming an adequate SNR. Future studies in patients with kidney diseases are required to determine the value of DKI for functional kidney imaging.

Keywords: Anisotropy; DKI; DTI; DWI; Diffusion; Kidney; Kurtosis.

MeSH terms

  • Adult
  • Algorithms*
  • Body Water / metabolism*
  • Computer Simulation
  • Diffusion Magnetic Resonance Imaging / methods*
  • Feasibility Studies
  • Female
  • Humans
  • Image Enhancement / methods*
  • Image Interpretation, Computer-Assisted / methods*
  • Kidney / anatomy & histology*
  • Kidney / metabolism*
  • Male
  • Models, Biological
  • Observer Variation
  • Reproducibility of Results
  • Sensitivity and Specificity