Skip to main content

Advertisement

SpringerLink
Log in

Evaluating the clinical value of MRI multi-model diffusion-weighted imaging on liver fibrosis in chronic hepatitis B patients

  • Hepatobiliary
  • Published:
Abdominal Radiology Aims and scope Submit manuscript

Abstract

Purpose

To explore the value of various diffusion parameters obtained from monoexponential, biexponential, and stretched exponential in assessing liver fibrosis in chronic hepatitis B (CHB).

Methods

DWI and intravoxel incoherent motion (IVIM) MRI were performed prospectively on liver for 146 patients with CHB and 21 healthy volunteers. ADC values were obtained from monoexponential model imaging. Diffusion coefficient (D), pseudodiffusion coefficient (D*), and perfusion fraction (f) obtained by biexponential model imaging, and stretched exponential model to obtain diffusion distribution coefficient (DDC) and diffusion heterogeneity index (α). Blood draw were performed on patients to obtain AST, ALT, and PLT, and then APRI and FIB-4 index were determined based on the serological diagnostic models. The fibrosis stage was staged (S0–S4) according to the pathology of liver puncture. Independent sample t test was used to compare the parameter values between liver fibrosis group and control group. One-way ANOVA was used to compare the parameters of different liver fibrosis grades. Bonferroni test was used for correcting multiple comparisons. Spearman correlation was used to analyze the correlation between each parameter and liver fibrosis grades. ROC was used to predict the diagnostic power of each parameter for liver fibrosis stages ≥ S2 and ≥ S3.

Results

ADC, D, D*, f, and DDC values were significantly different between normal control group and hepatic fibrosis group (P < 0.05). There were significant differences in ADC, D*, f, and DDC value among liver fibrosis groups (P < 0.05). D* and DDC values were moderately negatively correlated with the grades of liver fibrosis (r =  − 0.483, P < 0.001; r =  − 0.622, P < 0.001). ADC and f values were slightly negatively correlated with the grades of liver fibrosis (r =  − 0.295, P < 0.001; r =  − 0.312, P < 0.001). DDC values have the highest diagnostic efficiency in liver fibrosis stages ≥ S2 and ≥ S3. The areas under ROC curve (AUC) were 0.813 and 0.832 for ≥ S2 and ≥ S3, respectively, the sensitivity is 83.72% and 73.53%, and the specificity of 83.33% and 66.04%, which were better than APRI and FIB-4.

Conclusion

D* obtained from biexponential and DDC obtained from stretched exponential DWI have better value in evaluating the degree of liver fibrosis in CHB.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5

Similar content being viewed by others

References

  1. Liaw YF, Kao JH, Piratvisuth T, et al. Erratum to: Asian-Pacific consensus statement on the management of chronic hepatitis B: a 2012 update[J]. Hepatol Int, 2012, 6(4): 809-810. https://doi.org/10.1007/s12072-012-9386-z

    Article  Google Scholar 

  2. Chow AM, Gao DS, Fan SJ, et al. Liver fibrosis: an intravoxel incoherent motion (IVIM) study[J]. Magn Reson Imaging, 2012, 36(1): 159-167.PMID: 22334528.

    Article  Google Scholar 

  3. Shi Y, Guo QY, Fu XX, et al. Standardized apparent diffusion coefficient of 3.0T MR in evaluating the degree of liver fibrosis [J]. Chin J Radiol, 2012,46: 322–326.

  4. Cece H, Ercan A, Yιldιz S, et al. The use of DWI to assess spleen and liver quantitative ADC changes in the detection of liver fibrosis stages in chronic viral hepatitis[J]. Eur J Radiol, 2013, 82(8): e307-e312.

    Article  Google Scholar 

  5. Zou LQ, Pan J, Cheng XY, et al. Value of MR susceptibility-weighted imaging in the diagnosis of hepatic fibrosis grading in rabbits [J].Chin J Radiol, 2015,49 (8): 615–618.

  6. Fan GH, Gong JP, Shen JK, et al. Value of MR diffusion-weighted imaging in diagnosis of liver fibrosis in rats [J]. Chin J Radiol, 2013,47 (2): 172-177.

    Google Scholar 

  7. Koh DM, Collins DJ, Orton MR, et al. Intravoxel incoherent motion in body diffusion-weighted MRI: reality and challenges[J]. AJR, 2011,196(6):1351-1361.

    Article  Google Scholar 

  8. Taouli B, Vilgrain V, Dumont E, Daire JL, Fan B, Menu Y. Evaluation of liver diffusion isotropy and characterization of focal hepatic lesions with two single-shot echo-planar MR imaging sequences: prospective study in 66 patients. Radiology. 2003. 226(1): 71-8

    Article  Google Scholar 

  9. Chinese Society of Hepatology, Chinese Society of Infectious Diseases, Chinese Medical Association. Guideline for prevention and treatment of chronic hepatitis B [J]. Chinese Journal of Hepatology: Electronic Edition, 2015,7 (3): 1–18.

  10. Sterling RK, Lissen E, Clumeck N, et al. Development of a simple noninvasive index to predict significant fibrosis in patients with HIV/HCV confection[J]. Hepatology, 2006,43:1317-1325.

    Article  CAS  Google Scholar 

  11. Wai CT, Greenson JK, Fontana RJ, et al. A simple noninvasive index can predict both significant fibrosis and cirrhosis in patients with chronic hepatitis C[J]. Hepatology, 2003,38:518-526.

    Article  Google Scholar 

  12. Kumar M, Sarin SK. Is cirrhosis of the liver reversible[J] Indian J Pediatr,2007,74(4): 393–399.

  13. Luciani A, Vignaud A, Cavet M, Nhieu JT, Mallat A, Ruel L, et al. Liver cirrhosis: intravoxel incoherent motion MR imaging--pilot study[J]. Radiology. 2009,249(3):891-9.

    Article  Google Scholar 

  14. Huseyin O, Firat K, Ozan K, et al. Diffusion Weighted MRI for Hepatic Fibrosis: impact of b-Value. Iran J Radiol, 2014, 11(1): e3555.

    Google Scholar 

  15. Klauss M, Mayer P, Maier-Hein K, etal. IVIM-diffusion-MRI for the differentiation of solid begin and malign hypervascular liver lesions-evaluation with two different MR scanner[J]. EurJ Radiol,2016,85(7):1289-1294.

    Article  Google Scholar 

  16. Tokgoz O, Unal I, Turgut GG, et al. The value of liver and spleen ADC measurements in the diagnosis and follow up of hepatic fibrosis in chronic liver disease. Acta clinica Belgica, 2014, 69(6): 426-432.

    Article  CAS  Google Scholar 

  17. Amona L, Wurnig MC, Luechinger R, et al. Whole-body intravoxel incoherent motion imaging [J]. Eur Radiol,2015,25(7):2049-2058.

    Article  Google Scholar 

  18. Lazar M, Jensen JH, Xuan L, Helpern JA. Estimation of the orientation distribution function from diffusional kurtosis imaging. Magn Reson Med. 2008. 60(4): 774-81.

    Article  Google Scholar 

  19. Cohen Y, Assaf Y. High b-value q-space analyzed diffusion-weighted MRS and MRI in neuronal tissues - a technical review. NMR Biomed. 2002. 15(7-8): 516-542.

    Article  Google Scholar 

  20. Anderson SW, Barry B, Soto J, Ozonoff A, O'Brien M, Jara H. Characterizing non-gaussian, high b-value diffusion in liver fibrosis: Stretched exponential and diffusional. 39(4): 827–34.

  21. Xie Lf, Liang Ch. Research progress of intratosomal incoherent motor imaging in liver [J]. Chinese journal of radiology. 2014,48 (1): 77-9.

    Google Scholar 

  22. Le Bihan D, Turner R, Macfall JR, et al. Effects of intravoxel incoherent motions (IVIM) in steady-state free precession (SSFP) imaging: application to molecular diffusion imaging[J]. Magn Reson Med, 1989, 10(3): 324-337.PMID: 2733589.

    Article  Google Scholar 

  23. Zeng Z, Lu BP, Huang H. The preliminary study on the diagnosis of liver fibrosis with intra-voxel incoherent motion imaging [J]. Radiology Practice. 2015 (7): 775-8.

    Google Scholar 

  24. Walter SS, Liu W, Stemmer A, et al. Combination of integrated dynamic shimming and readout-segmented echo planar imaging for diffusion weighted MRI of the head and neck region at 3 Tesla. Magn Reson Imaging, 2017, 42: 32-36.

    Article  Google Scholar 

  25. Li C, Zhu SC, Zhang DX, et al. Value of intra-voxel incoherent motion diffusion-weighted MR imaging in evaluating the degree of liver fibrosis in patients with chronic hepatitis B. Magnetic Resonance Imaging, 2017,8 (9): 662-667.

    CAS  Google Scholar 

  26. Andreou A, Koh DM, Collins DJ, et al. Measurement reproducibility of perfusion fraction and pseudodiffusion coefficient derived by intravoxel incoherent motion diffusion-weighted MR imaging in normal liver and metastases[J]. Eur Radial,2012,23:428-434

  27. Sigmund EE, Vivier PH, Sui D, et al. Intravoxel incoherent motion and diffusion-tensor imaging in renal tissue under hydration and furosemide flow challenges[J]. Radiology,2012,263.

  28. Orton MR, Collins DJ, Koh DM, Leach MO. Improved intravoxel incoherent motion analysis of diffusion weighted imaging by data driven Bayesian modeling. Magn Reson Med. 2014;71(1):411-420.

    Article  Google Scholar 

Download references

Funding

Beijing Municipal Science & Technology Commission (Z181100001718006).

Author information

Author notes

  1. Hongwei Ren, Yuan Liu and Jing Lu have contributed this manuscript equally.

Authors and Affiliations

  1. Department of Radiology, Fifth Medical Center of Chinese PLA General Hospital, Beijing, 100039, People’s Republic of China

    Hongwei Ren, Yuan Liu, Weimin An, Jinghui Dong & Jianming Cai

  2. Department of Radiology, Fourth Medical Center of Chinese PLA General Hospital, Beijing, 100048, People’s Republic of China

    Jing Lu

  3. Department of Ultrasound, Beijing Tiantan Hospital, Capital Medical University, Beijing, 100070, People’s Republic of China

    Weidi Wang

  4. International Liver Diseases Diagnosis and Treatment Center, Fifth Medical Center of Chinese PLA General Hospital, Beijing, 100039, People’s Republic of China

    Tao Yan

  5. Fengbeiqiao Outpatient Department of Jingnan Medical Center, Chinese PLA General Hospital, Beijing, 100039, People’s Republic of China

    Yunfang Li

Authors
  1. Hongwei Ren
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Yuan Liu
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Jing Lu
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Weimin An
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Weidi Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Tao Yan
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Yunfang Li
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Jinghui Dong
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Jianming Cai
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding authors

Correspondence to Jinghui Dong or Jianming Cai.

Ethics declarations

Conflict of interest

The authors declared no conflicts of interest.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Ren, H., Liu, Y., Lu, J. et al. Evaluating the clinical value of MRI multi-model diffusion-weighted imaging on liver fibrosis in chronic hepatitis B patients. Abdom Radiol 46, 1552–1561 (2021). https://doi.org/10.1007/s00261-020-02806-x

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00261-020-02806-x

Keywords

Search

Navigation