Skip to main content

Advertisement

SpringerLink
Log in

Combination of hepatocyte fraction and diffusion-weighted imaging as a predictor in quantitative hepatic fibrosis evaluation

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

Abstract

Objective

To investigate the performance of the combined hepatocyte fraction (HepF) and apparent diffusion coefficient (ADC) values to stage hepatic fibrosis (HF) in patients with hepatitis B/C.

Materials and methods

A total of 281 patients with hepatitis B/C prospectively underwent gadoxetate disodium-based T1 mapping and diffusion-weighted imaging. HepF was determined from pre and postcontrast T1 mapping with pharmacokinetics. The independent predictors of the HF stage (S0–4) were identified from HepF, ADC, conventional T1-based parameters, and age using a logistic regression analysis. The performances of independent and combined predictors in diagnosing various HF stages were compared by analyzing receiver operating characteristic curves. The intraclass correlation coefficient (ICC) was used to assess the interobserver reproducibility of each predictor.

Results

In total, 167 patients with various stages of HF were included. All measurements had excellent interobserver agreement (ICC ≥ 0.75). The hepatic relative enhancement, HepF ,and ADC values were significantly different among various HF stages (p < 0.05). The HepF and ADC were independent predictors of > S0, > S1, > S2 , and > S3 disease (p < 0.05). T1Liver, T1Spleen, and T1Liver/Spleen were independent predictors of S > 2 disease (p < 0.05). The performance of HepF combined with the ADC (area under the curve (AUC) = 0.84–0.95) was higher than HepF (AUC = 0.79–0.92) or ADC (AUC = 0.82–0.89) alone in diagnosing > S0, > S1, > S2 , and > S3 disease.

Conclusion

The combined predictor of HepF and ADC shows acceptable performance for staging HF.

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

Similar content being viewed by others

References

  1. P. Lampertico, M. Maini, G. Papatheodoridis, Optimal management of hepatitis B virus infection – EASL Special Conference, J. Hepatol. 63 (2015) 1238–1253. https://doi.org/10.1016/j.jhep.2015.06.026.

  2. J.M. Pawlotsky, A. Aghemo, D. Back, G. Dusheiko, X. Forns, M. Puoti, C. Sarrazin, EASL Recommendations on Treatment of Hepatitis C 2015, J. Hepatol. 63 (2015) 199–236. https://doi.org/10.1016/j.jhep.2015.03.025.

  3. P. Bedossa, F. Carrat, Liver biopsy: The best, not the gold standard, J. Hepatol. 50 (2009) 1–3. https://doi.org/10.1016/j.jhep.2008.10.014.

  4. D.C. Rockey, S.H. Caldwell, Z.D. Goodman, R.C. Nelson, A.D. Smith, American Association for the Study of Liver Diseases, Liver biopsy., Hepatology. 49 (2009) 1017–44. https://doi.org/10.1002/hep.22742.

  5. T. Lefebvre, C. Wartelle-Bladou, P. Wong, G. Sebastiani, J.-M. Giard, H. Castel, J. Murphy-Lavallée, D. Olivié, A. Ilinca, M.-P. Sylvestre, G. Gilbert, Z.-H. Gao, B.N. Nguyen, G. Cloutier, A. Tang, Prospective comparison of transient, point shear wave, and magnetic resonance elastography for staging liver fibrosis, Eur. Radiol. 29 (2019) 6477–6488. https://doi.org/10.1007/s00330-019-06331-4.

  6. N.H. Afdhal, B.R. Bacon, K. Patel, E.J. Lawitz, S.C. Gordon, D.R. Nelson, T.L. Challies, I. Nasser, J. Garg, L.-J. Wei, J.G. McHutchison, Accuracy of Fibroscan, Compared With Histology, in Analysis of Liver Fibrosis in Patients With Hepatitis B or C: A United States Multicenter Study, Clin. Gastroenterol. Hepatol. 13 (2015) 772-779.e3. https://doi.org/10.1016/j.cgh.2014.12.014.

  7. S. Singh, S.K. Venkatesh, Z. Wang, F.H. Miller, U. Motosugi, R.N. Low, T. Hassanein, P. Asbach, E.M. Godfrey, M. Yin, J. Chen, A.P. Keaveny, M. Bridges, A. Bohte, M.H. Murad, D.J. Lomas, J.A. Talwalkar, R.L. Ehman, Diagnostic Performance of Magnetic Resonance Elastography in Staging Liver Fibrosis: A Systematic Review and Meta-analysis of Individual Participant Data, Clin. Gastroenterol. Hepatol. 13 (2015) 440-451.e6. https://doi.org/10.1016/j.cgh.2014.09.046.

  8. K. Juluru, A.H. Talal, R.K. Yantiss, P. Spincemaille, E.K. Weidman, A.E. Giambrone, S. Jalili, S.P. Sourbron, J.P. Dyke, Diagnostic accuracy of intracellular uptake rates calculated using dynamic Gd-EOB-DTPA-enhanced MRI for hepatic fibrosis stage, J. Magn. Reson. Imaging. 45 (2017) 1177–1185. https://doi.org/10.1002/jmri.25431.

  9. N. Tsuda, O. Matsui, Cirrhotic Rat Liver: Reference to Transporter Activity and Morphologic Changes in Bile Canaliculi—Gadoxetic Acid–enhanced MR Imaging, Radiology. 256 (2010) 767–773. https://doi.org/10.1148/radiol.10092065.

  10. J.B. Chakraborty, F. Oakley, M.J. Walsh, Mechanisms and Biomarkers of Apoptosis in Liver Disease and Fibrosis, Int. J. Hepatol. 2012 (2012) 1–10. https://doi.org/10.1155/2012/648915.

  11. M.J. Walsh, D.M. Vanags, A.D. Clouston, M.M. Richardson, D.M. Purdie, J.R. Jonsson, E.E. Powell, Steatosis and liver cell apoptosis in chronic hepatitis C: A mechanism for increased liver injury, Hepatology. 39 (2004) 1230–1238. https://doi.org/10.1002/hep.20179.

  12. P.J. Scheuer, Classification of chronic viral hepatitis: a need for reassessment, J. Hepatol. 13 (1991) 372–374. https://doi.org/10.1016/0168-8278(91)90084-O.

  13. O. Dahlqvist Leinhard, N. Dahlström, J. Kihlberg, P. Sandström, T.B. Brismar, Ö. Smedby, P. Lundberg, Quantifying differences in hepatic uptake of the liver specific contrast agents Gd-EOB-DTPA and Gd-BOPTA: a pilot study, Eur. Radiol. 22 (2012) 642–653. https://doi.org/10.1007/s00330-011-2302-4.

  14. D.G. Levitt, The pharmacokinetics of the interstitial space in humans., BMC Clin. Pharmacol. 3 (2003) 3. https://doi.org/10.1186/1472-6904-3-3.

  15. Y. Ding, S.-X. Rao, T. Zhu, C.-Z. Chen, R.-C. Li, M.-S. Zeng, Liver fibrosis staging using T1 mapping on gadoxetic acid-enhanced MRI compared with DW imaging, Clin. Radiol. 70 (2015) 1096–1103. https://doi.org/10.1016/j.crad.2015.04.014.

  16. S. Pan, X.-Q. Wang, Q.-Y. Guo, Quantitative assessment of hepatic fibrosis in chronic hepatitis B and C: T1 mapping on Gd-EOB-DTPA-enhanced liver magnetic resonance imaging, World J. Gastroenterol. 24 (2018) 2024–2035. https://doi.org/10.3748/wjg.v24.i18.2024.

  17. R.F. Sheng, H.Q. Wang, L. Yang, K.P. Jin, Y.H. Xie, C.X. Fu, M.S. Zeng, Assessment of liver fibrosis using T1 mapping on Gd-EOB-DTPA-enhanced magnetic resonance, Dig. Liver Dis. 49 (2017) 789–795. https://doi.org/10.1016/j.dld.2017.02.006.

  18. L. Yang, S. Rao, W. Wang, C. Chen, Y. Ding, C. Yang, R. Grimm, X. Yan, C. Fu, M. Zeng, Staging liver fibrosis with DWI: is there an added value for diffusion kurtosis imaging?, Eur. Radiol. 28 (2018) 3041–3049. https://doi.org/10.1007/s00330-017-5245-6.

  19. Shin, Song, Hwang, Hwang, Kim, Moon, Liver Fibrosis Assessment with Diffusion-Weighted Imaging: Value of Liver Apparent Diffusion Coefficient Normalization Using the Spleen as a Reference Organ, Diagnostics. 9 (2019) 107. https://doi.org/10.3390/diagnostics9030107.

  20. R. Reiter, C. Freise, K. Jöhrens, C. Kamphues, D. Seehofer, M. Stockmann, R. Somasundaram, P. Asbach, J. Braun, A. Samani, I. Sack, Wideband MRE and static mechanical indentation of human liver specimen: Sensitivity of viscoelastic constants to the alteration of tissue structure in hepatic fibrosis, J. Biomech. 47 (2014) 1665–1674. https://doi.org/10.1016/j.jbiomech.2014.02.034.

  21. K. Imajo, T. Kessoku, Y. Honda, W. Tomeno, Y. Ogawa, H. Mawatari, K. Fujita, M. Yoneda, M. Taguri, H. Hyogo, Y. Sumida, M. Ono, Y. Eguchi, T. Inoue, T. Yamanaka, K. Wada, S. Saito, A. Nakajima, Magnetic Resonance Imaging More Accurately Classifies Steatosis and Fibrosis in Patients With Nonalcoholic Fatty Liver Disease Than Transient Elastography, Gastroenterology. 150 (2016) 626-637.e7. https://doi.org/10.1053/j.gastro.2015.11.048.

  22. M. Toguchi, M. Tsurusaki, N. Yada, K. Sofue, T. Hyodo, M. Onoda, I. Numoto, M. Matsuki, I. Imaoka, M. Kudo, T. Murakami, Magnetic resonance elastography in the assessment of hepatic fibrosis: a study comparing transient elastography and histological data in the same patients, Abdom. Radiol. 42 (2017) 1659–1666. https://doi.org/10.1007/s00261-017-1045-3.

  23. H.A. Dyvorne, G.H. Jajamovich, O. Bane, M.I. Fiel, H. Chou, T.D. Schiano, D. Dieterich, J.S. Babb, S.L. Friedman, B. Taouli, Prospective comparison of magnetic resonance imaging to transient elastography and serum markers for liver fibrosis detection, Liver Int. 36 (2016) 659–666. https://doi.org/10.1111/liv.13058.

  24. A. Srinivasa Babu, M.L. Wells, O.M. Teytelboym, J.E. Mackey, F.H. Miller, B.M. Yeh, R.L. Ehman, S.K. Venkatesh, Elastography in Chronic Liver Disease: Modalities, Techniques, Limitations, and Future Directions, RadioGraphics. 36 (2016) 1987–2006. https://doi.org/10.1148/rg.2016160042.

  25. M. Hirooka, Y. Koizumi, Y. Hiasa, M. Abe, Y. Ikeda, B. Matsuura, M. Onji, Hepatic Elasticity in Patients With Ascites: Evaluation With Real-Time Tissue Elastography, Am. J. Roentgenol. 196 (2011) W766–W771. https://doi.org/10.2214/AJR.10.4867.

  26. Z. Almpanis, M. Demonakou, D. Tiniakos, Evaluation of liver fibrosis: “Something old, something new…,” Ann. Gastroenterol. 29 (2016) 445–453. https://doi.org/10.20524/aog.2016.0046.

  27. E. Kocakoc, A.A. Bakan, O.K. Poyrazoglu, A.F. Dagli, Y. Gul, M. Cicekci, I.H. Bahcecioglu, Assessment of Liver Fibrosis with Diffusion-Weighted Magnetic Resonance Imaging Using Different b-values in Chronic Viral Hepatitis, Med. Princ. Pract. 24 (2015) 522–526. https://doi.org/10.1159/000434682.

  28. A. Regev, Sampling error and intraobserver variation in liver biopsy in patients with chronic HCV infection, Am. J. Gastroenterol. 97 (2002) 2614–2618. https://doi.org/10.1016/S0002-9270(02)04396-4.

Download references

Funding

The Medical Science and Technology Research Foundation of Guangdong Province (Grant No. A2018025).

Author information

Authors and Affiliations

  1. Department of Radiology, Jiangmen Central Hospital, Affiliated Jiangmen Central Hospital of Guangdong Medical University, Affiliated Jiangmen Hospital of SUN YAT-SEN University, 23 Beijie Haibang Street, Jiangmen, 529030, People’s Republic of China

    Enming Cui, Wansheng Long, Zhuoyong Li & Yong Lan

  2. Department of Pathology, Jiangmen Central Hospital, Affiliated Jiangmen Hospital of SUN YAT-SEN University, 23 Beijie Haibang Street, Jiangmen, 529030, People’s Republic of China

    Qing Li

  3. Department of Hepatobiliary Surgery, Jiangmen Central Hospital, Affiliated Jiangmen Hospital of SUN YAT-SEN University, 23 Beijie Haibang Street, Jiangmen, 529030, People’s Republic of China

    Juanhua Wu

  4. Healthcare, Philips, 18F, Tower B, China International Center, No.33 Zhongshansan Road, Yuexiu District, Guangzhou, 510055, People’s Republic of China

    Yingjie Mei

  5. Department of Radiology, The First Affiliated Hospital of Shenzhen University, Health Science Center, Shenzhen Second People’s Hospital, 3002 SunGangXi Road, Shenzhen, 518035, People’s Republic of China

    Juan Yu & Fan Lin

Authors
  1. Enming Cui
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Qing Li
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Juanhua Wu
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Yingjie Mei
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Juan Yu
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Wansheng Long
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Zhuoyong Li
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Yong Lan
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Fan Lin
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Fan Lin.

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

Cui, E., Li, Q., Wu, J. et al. Combination of hepatocyte fraction and diffusion-weighted imaging as a predictor in quantitative hepatic fibrosis evaluation. Abdom Radiol 45, 3681–3689 (2020). https://doi.org/10.1007/s00261-020-02520-8

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00261-020-02520-8

Keywords

Search

Navigation