Skip to main content
SpringerLink
Log in

The effect of hepatic steatosis on liver volume determined by proton density fat fraction and deep learning–measured liver volume

  • Gastrointestinal
  • Published:
European Radiology Aims and scope Submit manuscript

Abstract

Objectives

We aimed to evaluate the effect of hepatic steatosis (HS) on liver volume and to develop a formula to estimate lean liver volume correcting the HS effect.

Methods

This retrospective study included healthy adult liver donors who underwent gadoxetic acid–enhanced MRI and proton density fat fraction (PDFF) measurement from 2015 to 2019. The degree of HS was graded at 5% PDFF intervals from grade 0 (no HS; PDFF < 5.5%). Liver volume was measured with hepatobiliary phase MRI using deep learning algorithm, and standard liver volume (SLV) was calculated as the reference lean liver volume. The association between liver volume and SLV ratio with PDFF grades was evaluated using Spearman’s correlation (ρ). The effect of PDFF grades on liver volume was evaluated using the multivariable linear regression model.

Results

The study population included 1038 donors (mean age, 31 ± 9 years; 689 men). Mean liver volume to SLV ratio increased according to PDFF grades (ρ = 0.234, p < 0.001). The multivariable analysis indicated that SLV (β = 1.004, p < 0.001) and PDFF grade*SLV (β = 0.044, p < 0.001) independently affected liver volume, suggesting a 4.4% increase in liver volume per one-point increment in the PDFF grade. PDFF-adjusted lean liver volume was estimated using the formula, liver volume/[1.004 + 0.044 × PDFF grade]. The mean estimated lean liver volume to SLV ratio approximated to one for all PDFF grades, with no significant association with PDFF grades (p = 0.851).

Conclusion

HS increases liver volume. The formula to estimate lean liver volume may be useful to adjust for the effect of HS on liver volume.

Key Points

• Hepatic steatosis increases liver volume.

• The presented formula to estimate lean liver volume using MRI-measured proton density fat fraction and liver volume may be useful to adjust for the effect of hepatic steatosis on measured liver volume.

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

Abbreviations

HBP:

Hepatobiliary phase

HS:

Hepatic steatosis

LDLT:

Living donor liver transplantation

PDFF:

Proton density fat fraction

SLV:

Standard liver volume

References

  1. Schindl MJ, Redhead DN, Fearon KC et al (2005) The value of residual liver volume as a predictor of hepatic dysfunction and infection after major liver resection. Gut 54:289–296. https://doi.org/10.1136/gut.2004.046524

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  2. Prodeau M, Drumez E, Duhamel A et al (2019) An ordinal model to predict the risk of symptomatic liver failure in patients with cirrhosis undergoing hepatectomy. J Hepatol 71:920–929. https://doi.org/10.1016/j.jhep.2019.06.003

    Article  PubMed  Google Scholar 

  3. Kiuchi T, Kasahara M, Uryuhara K et al (1999) Impact of graft size mismatching on graft prognosis in liver transplantation from living donors. Transplantation 67:321–327. https://doi.org/10.1097/00007890-199901270-00024

    Article  CAS  PubMed  Google Scholar 

  4. Ahn Y, Yoon JS, Lee SS et al (2020) Deep learning algorithm for automated segmentation and volume measurement of the liver and spleen using portal venous phase computed tomography images. Korean J Radiol 21:987–997. https://doi.org/10.3348/kjr.2020.0237

    Article  PubMed  PubMed Central  Google Scholar 

  5. Park HJ, Yoon JS, Lee SS et al (2022) Deep learning-based assessment of functional liver capacity using gadoxetic acid-enhanced hepatobiliary phase MRI. Korean J Radiol 23:720–731. https://doi.org/10.3348/kjr.2021.0892

    Article  PubMed  PubMed Central  Google Scholar 

  6. Wong VW, Wong GL, Yeung DK et al (2015) Incidence of non-alcoholic fatty liver disease in Hong Kong: a population study with paired proton-magnetic resonance spectroscopy. J Hepatol 62:182–189. https://doi.org/10.1016/j.jhep.2014.08.041

    Article  PubMed  Google Scholar 

  7. Younossi ZM, Blissett D, Blissett R et al (2016) The economic and clinical burden of nonalcoholic fatty liver disease in the United States and Europe. Hepatology 64:1577–1586. https://doi.org/10.1002/hep.28785

    Article  PubMed  Google Scholar 

  8. Raptis DA, Fischer MA, Graf R et al (2012) MRI: the new reference standard in quantifying hepatic steatosis? Gut 61:117–127. https://doi.org/10.1136/gutjnl-2011-300155

    Article  PubMed  Google Scholar 

  9. Bannas P, Kramer H, Hernando D et al (2015) Quantitative magnetic resonance imaging of hepatic steatosis: validation in ex vivo human livers. Hepatology 62:1444–1455. https://doi.org/10.1002/hep.28012

    Article  CAS  PubMed  Google Scholar 

  10. Yki-Jarvinen H (2014) Non-alcoholic fatty liver disease as a cause and a consequence of metabolic syndrome. Lancet Diabetes Endocrinol 2:901–910. https://doi.org/10.1016/S2213-8587(14)70032-4

    Article  CAS  PubMed  Google Scholar 

  11. Behrns KE, Tsiotos GG, DeSouza NF, Krishna MK, Ludwig J, Nagorney DM (1998) Hepatic steatosis as a potential risk factor for major hepatic resection. J Gastrointest Surg 2:292–298. https://doi.org/10.1016/s1091-255x(98)80025-5

    Article  CAS  PubMed  Google Scholar 

  12. Vetelainen R, van Vliet A, Gouma DJ, van Gulik TM (2007) Steatosis as a risk factor in liver surgery. Ann Surg 245:20–30. https://doi.org/10.1097/01.sla.0000225113.88433.cf

    Article  PubMed  PubMed Central  Google Scholar 

  13. Chen TY, Chen CL, Tsang LL et al (2008) Correlation between hepatic steatosis, hepatic volume, and spleen volume in live liver donors. Transplant Proc 40:2481–2483. https://doi.org/10.1016/j.transproceed.2008.08.045

    Article  PubMed  Google Scholar 

  14. Tang A, Chen J, Le TA et al (2015) Cross-sectional and longitudinal evaluation of liver volume and total liver fat burden in adults with nonalcoholic steatohepatitis. Abdom Imaging 40:26–37. https://doi.org/10.1007/s00261-014-0175-0

    Article  PubMed  PubMed Central  Google Scholar 

  15. Luo RB, Suzuki T, Hooker JC et al (2018) How bariatric surgery affects liver volume and fat density in NAFLD patients. Surg Endosc 32:1675–1682. https://doi.org/10.1007/s00464-017-5846-9

    Article  PubMed  Google Scholar 

  16. Bian H, Hakkarainen A, Zhou Y, Lundbom N, Olkkonen VM, Yki-Jarvinen H (2015) Impact of non-alcoholic fatty liver disease on liver volume in humans. Hepatol Res 45:210–219. https://doi.org/10.1111/hepr.12338

    Article  CAS  PubMed  Google Scholar 

  17. Kromrey ML, Ittermann T, vWahsen C, et al (2018) Reference values of liver volume in Caucasian population and factors influencing liver size. Eur J Radiol 106:32–37. https://doi.org/10.1016/j.ejrad.2018.07.005

    Article  CAS  PubMed  Google Scholar 

  18. Eshraghian A, Rasekhi A, Nikeghbalian S et al (2022) Hepatic computed tomography volumetry for noninvasive detection of hepatic steatosis and steatohepatitis in living liver donors. Exp Clin Transplant 20:388–394. https://doi.org/10.6002/ect.2019.0089

    Article  PubMed  Google Scholar 

  19. Siriwardana RC, Chan SC, Chok KS, Lo CM, Fan ST (2011) Effects of the liver volume and donor steatosis on errors in the estimated standard liver volume. Liver Transpl 17:1437–1442. https://doi.org/10.1002/lt.22430

    Article  PubMed  Google Scholar 

  20. Ha Y, Shim JH, Song GW et al (2017) Role of computed tomography volumetry in estimating liver weights in surgical patients with hepatic steatosis. Exp Clin Transplant 15:196–202. https://doi.org/10.6002/ect.2016.0065

    Article  PubMed  Google Scholar 

  21. Vauthey JN, Chaoui A, Do KA et al (2000) Standardized measurement of the future liver remnant prior to extended liver resection: methodology and clinical associations. Surgery 127:512–519. https://doi.org/10.1067/msy.2000.105294

    Article  CAS  PubMed  Google Scholar 

  22. Urata K, Kawasaki S, Matsunami H et al (1995) Calculation of child and adult standard liver volume for liver transplantation. Hepatology 21:1317–1321

    Article  CAS  PubMed  Google Scholar 

  23. Hashimoto T, Sugawara Y, Tamura S et al (2006) Estimation of standard liver volume in Japanese living liver donors. J Gastroenterol Hepatol 21:1710–1713. https://doi.org/10.1111/j.1440-1746.2006.04433.x

    Article  PubMed  Google Scholar 

  24. Poovathumkadavil A, Leung KF, Al Ghamdi HM, Othman Iel H, Meshikhes AW (2010) Standard formula for liver volume in Middle Eastern Arabic adults. Transplant Proc 42:3600–3605. https://doi.org/10.1016/j.transproceed.2010.07.098

    Article  CAS  PubMed  Google Scholar 

  25. Heinemann A, Wischhusen F, Puschel K, Rogiers X (1999) Standard liver volume in the Caucasian population. Liver Transpl Surg 5:366–368. https://doi.org/10.1002/lt.500050516

    Article  CAS  PubMed  Google Scholar 

  26. Kim DW, Ha J, Lee SS et al (2021) Population-based and personalized reference intervals for liver and spleen volumes in healthy individuals and those with viral hepatitis. Radiology 301:339–347. https://doi.org/10.1148/radiol.2021204183

    Article  PubMed  Google Scholar 

  27. Choi SH, Kim KW, Kwon HJ et al (2019) Clinical usefulness of gadoxetic acid-enhanced MRI for evaluating biliary anatomy in living donor liver transplantation. Eur Radiol 29:6508–6518. https://doi.org/10.1007/s00330-019-06292-8

    Article  PubMed  Google Scholar 

  28. Jang JK, Lee SS, Kim B et al (2019) Agreement and reproducibility of proton density fat fraction measurements using commercial mr sequences across different platforms: a multivendor, multi-institutional phantom experiment. Invest Radiol 54:517–523. https://doi.org/10.1097/RLI.0000000000000561

    Article  CAS  PubMed  Google Scholar 

  29. Zhong X, Nickel MD, Kannengiesser SA, Dale BM, Kiefer B, Bashir MR (2014) Liver fat quantification using a multi-step adaptive fitting approach with multi-echo GRE imaging. Magn Reson Med 72:1353–1365. https://doi.org/10.1002/mrm.25054

    Article  PubMed  Google Scholar 

  30. Ren J, Dimitrov I, Sherry AD, Malloy CR (2008) Composition of adipose tissue and marrow fat in humans by 1H NMR at 7 Tesla. J Lipid Res 49:2055–2062. https://doi.org/10.1194/jlr.D800010-JLR200

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Szczepaniak LS, Nurenberg P, Leonard D et al (2005) Magnetic resonance spectroscopy to measure hepatic triglyceride content: prevalence of hepatic steatosis in the general population. Am J Physiol Endocrinol Metab 288:E462-468. https://doi.org/10.1152/ajpendo.00064.2004

    Article  CAS  PubMed  Google Scholar 

  32. DuBois D, DuBois EF (1916) Clinical calorimetry: tenth paper a formula to estimate the approximate surface area if height and weight be known. Arch Intern Med 17:863–871. https://doi.org/10.1001/archinte.1916.00080130010002

    Article  CAS  Google Scholar 

  33. Mosteller RD (1987) Simplified calculation of body-surface area. N Engl J Med 317:1098. https://doi.org/10.1056/NEJM198710223171717

    Article  CAS  PubMed  Google Scholar 

  34. Kleiner DE, Brunt EM, Van Natta M et al (2005) Design and validation of a histological scoring system for nonalcoholic fatty liver disease. Hepatology 41:1313–1321. https://doi.org/10.1002/hep.20701

    Article  PubMed  Google Scholar 

  35. Tang A, Tan J, Sun M et al (2013) Nonalcoholic fatty liver disease: MR imaging of liver proton density fat fraction to assess hepatic steatosis. Radiology 267:422–431. https://doi.org/10.1148/radiol.12120896

    Article  PubMed  PubMed Central  Google Scholar 

  36. Yang X, Yang JD, Lee S et al (2018) Estimation of standard liver volume using CT volume, body composition, and abdominal geometry measurements. Yonsei Med J 59:546–553. https://doi.org/10.3349/ymj.2018.59.4.546

    Article  PubMed  PubMed Central  Google Scholar 

Download references

Funding

This research was supported by a National Research Foundation of Korea (NRF) grant, funded by the Korean Government (MSIT) (2020R1F1A1048826). National Research Foundation of Korea,2020R1F1A1048826,Seung Soo Lee

Author information

Authors and Affiliations

  1. Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Republic of Korea

    Ji Young Choi, Seung Soo Lee, Hyo Jung Park & Yu Sub Sung

  2. Department of Radiology, Kangbuk Samsung Hospital, Sungkyunkwan University College of Medicine, Seoul, Republic of Korea

    Ji Young Choi

  3. Department of Clinical Epidemiology and Biostatistics, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Republic of Korea

    Na Young Kim

  4. Department of Radiology, Haeundae Paik Hospital, Inje University College of Medicine, Busan, Republic of Korea

    Yedaun Lee

  5. Department of Brain and Cognitive Engineering, Korea University, Seoul, Republic of Korea

    Jee Seok Yoon & Heung-Il Suk

  6. Department of Artificial Intelligence, Korea University, Seoul, Republic of Korea

    Heung-Il Suk

Authors
  1. Ji Young Choi
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Seung Soo Lee
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Na Young Kim
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Hyo Jung Park
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Yu Sub Sung
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Yedaun Lee
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Jee Seok Yoon
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Heung-Il Suk
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Seung Soo Lee.

Ethics declarations

Guarantor

The scientific guarantor of this publication is Seung Soo Lee.

Conflict of interest

The authors declare that they have no conflict of interest.

Statistics and biometry

Na Young Kim kindly provided statistical advice for this manuscript.

Informed consent

Written informed consent was waived by the Institutional Review Board.

Ethical approval

Institutional Review Board approval was obtained.

Methodology

• retrospective

• observational

• performed at one institution

Additional information

Publisher's note

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

Supplementary Information

Below is the link to the electronic supplementary material.

Supplementary file1 (PDF 154 KB)

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Choi, J.Y., Lee, S.S., Kim, N.Y. et al. The effect of hepatic steatosis on liver volume determined by proton density fat fraction and deep learning–measured liver volume. Eur Radiol 33, 5924–5932 (2023). https://doi.org/10.1007/s00330-023-09603-2

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00330-023-09603-2

Keywords

Search

Navigation