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Diffusion kurtosis imaging in liver: a preliminary reproducibility study in healthy volunteers

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Magnetic Resonance Materials in Physics, Biology and Medicine Aims and scope Submit manuscript

Abstract

Objectives

To systematically test the reproducibility of DKI technique in normal liver and report a complete set of DKI measurement data.

Materials and methods

Thirty-two healthy volunteers were examined with liver DKI twice on the GE 3.0 T MRI scanner and reviewed by three professional experts. DKI-derived parameters fractional anisotropy of kurtosis (FAk), mean diffusivity (Md), axial diffusivity (Da), radial diffusivity (Dr), mean kurtosis (Mk), axial kurtosis (Ka), and radial kurtosis (Kr) in eight segments divided by Couinaud octagonal method were collected. Inter-class correlation coefficient (ICC) was used to assess the agreement between three experts. For each expert, the reproducibility of twice scans was evaluated by Bland–Altman method. Multivariate analysis of variance was to explore the regional distribution characteristics of DKI-derived parameters, and showed with box-plot graph.

Results

Using ICC analysis, except for FAk (ICC 0.312, 0.307), other DKI metric values showed high reproducibility (0.716 < ICC < 0.907) between three experts for each of two DKI measurements. With Bland–Altman method, liver segment 5 (S5) showed the best reproducibility between two DKI measurement, and the reproducibility of segment 4 (S4) was the worst. The reproducibility of the right lobe was significantly higher than the left lobe. The values of diffusion metrics (Md, Da, and Dr) and kurtosis metrics (Mk, Ka, and Kr) existed significantly difference between the right and left hepatic lobes.

Conclusion

DKI has shown excellent reproducibility in liver imaging. The range of values for multiple DKI parameters, derived from the normal liver, was reported, and may provide data reference for further clinical DKI applications. Additionally, DKI technique is a non-invasive method to reflect the perfusion or structural differences between the left and right hepatic lobes from the molecular level.

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References

  1. Jensen JH, Helpern JA, Lu H, Kaczynski K (2005) Diffusional kurtosis imaging: the quantification of non-gaussian water diffusion by means of magnetic resonance imaging. Magn Reson Med 53(6):1432–1440

    Article  Google Scholar 

  2. Jensen JH, Helpern JA (2010) MRI quantification of non-Gaussian water diffusion by kurtosis analysis. NMR Biomed 23(7):698–710

    Article  Google Scholar 

  3. Tan Y, Wang XC, Zhang H et al (2015) Differentiation of high-grade-astrocytomas from solitary-brain-metastases: comparing diffusion kurtosis imaging and diffusion tensor imaging. Eur J Radiol 84:2618–2624

    Article  Google Scholar 

  4. Wu EX (2010) MR diffusion kurtosis imaging for neural tissue characterization. NMR Biomed 23:836–848

    Article  Google Scholar 

  5. Yoshimaru D, Takatsu Y, Suzuki Y et al (2019) Diffusion kurtosis imaging in the assessment of liver function: its potential as an effective predictor of liver function. Br J Radiol 92(1094):20170608

    Article  Google Scholar 

  6. Goshima S, Kanematsu M, Noda Y et al (2015) Diffusion kurtosis imaging to assess response to treatment in hypervascular hepatocellular carcinoma. AJR 204:543–549

    Article  Google Scholar 

  7. Hu G, Liang W, Wu M, Chan Q, Li Y, Xu J et al (2018) Staging of rat liver fibrosis using monoexponential, stretched exponential and diffusion kurtosis models with diffusion weighted imaging-magnetic resonance. Oncotarget 9(2):2357–2366

    Article  Google Scholar 

  8. Yang L, Rao S, Wang W, Chen C, Ding Y, Yang C et al (2018) Staging liver fibrosis with DWI: is there an added value for diffusion kurtosis imaging? Eur Radiol 28(7):3041–3049

    Article  Google Scholar 

  9. Yoon JH, Lee JM, Lee KB et al (2019) Comparison of monoexponential, intravoxel incoherent motion diffusion-weighted imaging and diffusion kurtosis imaging for assessment of hepatic fibrosis. Acta Radiol 60:1593–1601

    Article  Google Scholar 

  10. Wang X, Xue HD, Jin ZY et al (2013) Quantitative hepatic CT perfusion measurement: comparison of Couinaud's hepatic segments with dual-source 128-slice CT. Eur J Radiol 82(2):220–226

    Article  Google Scholar 

  11. Kanda T, Yoshikawa T, Ohno Y, Fujisawa Y, Kanata N, Yamaguchi M et al (2012) Perfusion measurement of the whole upper abdomen of patients with and without liver diseases: initial experience with 320-detector row CT. Eur J Radiol 81:2470–2475

    Article  Google Scholar 

  12. Couinaud C (1999) Liver anatomy: portal (and suprahepatic) or biliary segmentation. Dig Surg 16(6):459–467

    Article  CAS  Google Scholar 

  13. Zhuo J, Keledjian K, Xu S et al (2015) Changes in diffusion kurtosis imaging and magnetic resonance spectroscopy in a direct cranial blast traumatic brain injury (dc-bTBI) model. PLoS One 10(8):e0136151

    Article  CAS  Google Scholar 

  14. Nasu K, Kuroki Y, Fujii H, Minami M (2007) Hepatic pseudo-anisotropy: a specific artifact in hepatic diffusion-weighted images obtained with respiratory triggering. Magn Reson Mater Phy 20(4):205–211

    Article  Google Scholar 

  15. Filli L, Wurnig M, Nanz D et al (2014) Whole-body diffusion kurtosis imaging: initial experience on non-Gaussian diffusion in various organs. Investig Radiol 49:773–778

    Article  Google Scholar 

  16. Yoshimaru D, Miyati T, Suzuki Y et al (2018) Diffusion kurtosis imaging with the breath-hold technique for staging hepatic fibrosis: a preliminary study. Magn Reson Imaging 47:33–38

    Article  Google Scholar 

  17. Fukunaga I, Hori M, Masutani Y et al (2013) Effects of diffusional kurtosis imaging parameters on diffusion quantification. Radiol Phys Technol 6(2):343–348

    Article  Google Scholar 

  18. Yanqi H, Xin C, Zhongping Z, Lifen Y, Dan P, Changhong L et al (2015) MRI quantification of non-Gaussian water diffusion in normal human kidney: a diffusional kurtosis imaging study. NMR Biomed 28(2):154–161

    Article  Google Scholar 

  19. ter Voert EE, Delso G, Porto M, Huellner M, Veit-Haibach PJIR (2016) Intravoxel incoherent motion protocol evaluation and data quality in normal and malignant liver tissue and comparison to the literature. Investig Radiol 51(2):90–99

    Article  Google Scholar 

  20. Hadrien D, Guido J, Suguru K, Bernd K, Bachir TJEJoR (2014) Intravoxel incoherent motion diffusion imaging of the liver: optimal b value subsampling and impact on parameter precision and reproducibility. Eur J Radiol 83(12):2109–2113

    Article  Google Scholar 

  21. Pasicz K, Podgórska J, Jasieniak J et al (2019) Optimal b values for diffusion kurtosis imaging of the liver and pancreas in MR examinations. Phys Med 66:119–123

    Article  Google Scholar 

  22. Bruegel M, Holzapfel K, Gaa J, Woertler K, Waldt S, Kiefer B et al (2008) Characterization of focal liver lesions by ADC measurements using a respiratory triggered diffusion-weighted single-shot echo-planar MR imaging technique. Eur Radiol 18(3):477–485

    Article  Google Scholar 

  23. Petra M, Sebastian F, Frank TB, Brink JS, Den V, Jürgen G, Schild HH (2002) Abdomen: diffusion-weighted MR imaging with pulse-triggered single-shot sequences. J Radiol 224(1):258

    Article  Google Scholar 

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Author notes

  1. Junying Wang and Weiqiang Dou have equally contributed for this work.

Authors and Affiliations

  1. Department of Medical Imaging, Shandong Provincial Qianfishan Hospital, The First Hospital Affiliated with Shandong First Medical University, No. 66, Jingshi Rd, Jinan, 250014, Shandong, China

    Junying Wang, Hao Shi, Yaping Ge & Haichao Cheng

  2. Shandong First Medical University, Taian, 271016, Shandong, China

    Junying Wang, Xiaoyi He & Huiyang Wang

  3. MR Research, GE Healthcare, Beijing, 10076, China

    Weiqiang Dou

Authors
  1. Junying Wang
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  2. Weiqiang Dou
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  3. Hao Shi
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  4. Xiaoyi He
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  5. Huiyang Wang
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  6. Yaping Ge
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  7. Haichao Cheng
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Contributions

JW: protocol/data collection/data analysis; WD: protocol/data analysis/project development; HS: protocol/data analysis/project development; HW: protocol/data collection; XH: project development; YG: data collection; HC: protocol/data analysis.

Corresponding author

Correspondence to Hao Shi.

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Conflict of interest

The authors each declare that they have no conflict of interest.

Ethical approval

All procedures performed in studies involving human participants were approved by the appropriate ethics committee of the First Affiliated Hospital of Shandong First Medical University.

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Informed consent was obtained from all individual participants included in the study.

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Wang, J., Dou, W., Shi, H. et al. Diffusion kurtosis imaging in liver: a preliminary reproducibility study in healthy volunteers. Magn Reson Mater Phy 33, 877–883 (2020). https://doi.org/10.1007/s10334-020-00846-4

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  • DOI: https://doi.org/10.1007/s10334-020-00846-4

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