Top

Published in:

Open Access 01-07-2018 | Original Article

Evaluation of liver function using gadolinium-ethoxybenzyl-diethylenetriamine pentaacetic acid enhanced magnetic resonance imaging based on a three-dimensional volumetric analysis system

Authors: Masashi Kudo, Naoto Gotohda, Motokazu Sugimoto, Tatsushi Kobayashi, Motohiro Kojima, Shinichiro Takahashi, Masaru Konishi, Ryuichi Hayashi

Published in: Hepatology International | Issue 4/2018

Abstract

Background

Magnetic resonance imaging with gadolinium-ethoxybenzyl-diethylenetriamine pentaacetic acid (EOB-MRI) is a diagnostic modality for liver tumors. Three-dimensional (3D) volumetric analysis systems using EOB-MRI data are used to simulate liver anatomy for surgery. This study was conducted to investigate clinical utility of a 3D volumetric analysis system on EOB-MRI to evaluate liver function.

Methods

Between August 2014 and December 2015, 181 patients underwent laboratory and radiological exams as standardized preoperative evaluation for liver surgery. The liver-spleen contrast-enhanced ratio (LSR) was measured by a semi-automated 3D volumetric analysis system on EOB-MRI. First, the inter-evaluator variability of the calculated LSR was evaluated. Additionally, a subset of liver surgical specimens was evaluated histologically by using immunohistochemical staining. Finally, the correlations between the LSR and grading systems of liver function, laboratory data, or histological findings were analyzed.

Results

The inter-evaluator correlation coefficient of the measured LSR was 0.986. The mean LSR was significantly correlated with the Child–Pugh score (p = 0.014) and the ALBI score (p < 0.001). Significant correlations were also observed between the LSR and indocyanine green retention rate at 15 min (r = − 0.601, p < 0.001), between the LSR and liver fibrosis stage (r = − 0.556, p < 0.001), and between the LSR and liver steatosis grade (r = − 0.396, p < 0.001).

Conclusion

The LSR calculated by a 3D volumetric analysis system on EOB-MRI was highly reproducible and was shown to be correlated with liver function parameters and liver histology. These data suggest that this imaging modality can be a reliable tool to evaluate liver function.

Available only for authorised users

Yadav K, Shrikhande S, Goel M. Post hepatectomy liver failure: concept of management. J Gastrointest Cancer. 2014;45(4):405–413. https://doi.org/10.1007/s12029-014-9646-3 Epub 2014/08/12.CrossRefPubMed

Huppertz A, Balzer T, Blakeborough A, Breuer J, Giovagnoni A, Heinz-Peer G, et al. Improved detection of focal liver lesions at MR imaging: multicenter comparison of gadoxetic acid-enhanced MR images with intraoperative findings. Radiology. 2004;230(1):266–275. https://doi.org/10.1148/radiol.2301020269 Epub 2003/12/26.CrossRefPubMed

Utsunomiya T, Shimada M, Hanaoka J, Kanamoto M, Ikemoto T, Morine Y, et al. Possible utility of MRI using Gd-EOB-DTPA for estimating liver functional reserve. J Gastroenterol. 2012;47(4):470–476. https://doi.org/10.1007/s00535-011-0513-8 Epub 2011/12/16.CrossRefPubMed

Matsushima S, Sato Y, Yamaura H, Kato M, Kinosada Y, Era S, et al. Visualization of liver uptake function using the uptake contrast-enhanced ratio in hepatobiliary phase imaging. Magn Reson Imaging. 2014;32(6):654–659. https://doi.org/10.1016/j.mri.2014.02.017 Epub 2014/03/19.CrossRefPubMed

Motosugi U, Ichikawa T, Sou H, Sano K, Tominaga L, Kitamura T, et al. Liver parenchymal enhancement of hepatocyte-phase images in Gd-EOB-DTPA-enhanced MR imaging: which biological markers of the liver function affect the enhancement? J Magn Reson Imaging. 2009;30(5):1042–1046. https://doi.org/10.1002/jmri.21956 Epub 2009/10/27.CrossRefPubMed

Motosugi U, Ichikawa T, Oguri M, Sano K, Sou H, Muhi A, et al. Staging liver fibrosis by using liver-enhancement ratio of gadoxetic acid-enhanced MR imaging: comparison with aspartate aminotransferase-to-platelet ratio index. Magn Reson Imaging. 2011;29(8):1047–1052. https://doi.org/10.1016/j.mri.2011.05.007 Epub 2011/07/22.CrossRefPubMed

Nishie A, Ushijima Y, Tajima T, Asayama Y, Ishigami K, Kakihara D, et al. Quantitative analysis of liver function using superparamagnetic iron oxide- and Gd-EOB-DTPA-enhanced MRI: comparison with technetium-99 m galactosyl serum albumin scintigraphy. Eur J Radiol. 2012;81(6):1100–1104. https://doi.org/10.1016/j.ejrad.2011.02.053 Epub 2011/03/26.CrossRefPubMed

Okada M, Murakami T, Kuwatsuru R, Nakamura Y, Isoda H, Goshima S, et al. Biochemical and clinical predictive approach and time point analysis of hepatobiliary phase liver enhancement on Gd-EOB-DTPA-enhanced MR images: a multicenter study. Radiology. 2016;281(2):474–483. https://doi.org/10.1148/radiol.2016151061 Epub 2016/05/20.CrossRefPubMed

Imura S, Shimada M, Utsunomiya T. Recent advances in estimating hepatic functional reserve in patients with chronic liver damage. Hepatol Res. 2015;45(1):10–19. https://doi.org/10.1111/hepr.12325 Epub 2014/03/13.CrossRefPubMed

10.

Bedossa P, Poynard T. An algorithm for the grading of activity in chronic hepatitis C. The METAVIR cooperative study group. Hepatology. 1996;24(2):289–293. https://doi.org/10.1002/hep.510240201 Epub 1996/08/01.CrossRefPubMed

11.

Sugimoto M, Takahashi S, Kojima M, Kobayashi T, Gotohda N, Konishi M. In patients with a soft pancreas, a thick parenchyma, a small duct, and fatty infiltration are significant risks for pancreatic fistula after pancreaticoduodenectomy. J Gastrointest Surg. 2017. https://doi.org/10.1007/s11605-017-3356-7.CrossRefPubMed

12.

Kleiner DE, Brunt EM, Van Natta M, Behling C, Contos MJ, Cummings OW, et al. Design and validation of a histological scoring system for nonalcoholic fatty liver disease. Hepatology. 2005;41(6):1313–1321. https://doi.org/10.1002/hep.20701 Epub 2005/05/26.CrossRefPubMed

13.

Ohshima S. Volume analyzer SYNAPSE VINCENT for liver analysis. J Hepatobiliary Pancreat Sci. 2014;21(4):235–238. https://doi.org/10.1002/jhbp.81 Epub 2014/02/13.CrossRefPubMed

14.

Mochizuki K, Takatsuki M, Soyama A, Hidaka M, Obatake M, Eguchi S. The usefulness of a high-speed 3D-image analysis system in pediatric living donor liver transplantation. Ann Transplant. 2012;17(1):31–34 Epub 2012/04/03.CrossRefPubMed

15.

Takamoto T, Hashimoto T, Ogata S, Inoue K, Maruyama Y, Miyazaki A, et al. Planning of anatomical liver segmentectomy and subsegmentectomy with 3-dimensional simulation software. Am J Surg. 2013;206(4):530–538. https://doi.org/10.1016/j.amjsurg.2013.01.041 Epub 2013/07/03.CrossRefPubMed

16.

Ogawa C, Minami Y, Morita M, Noda T, Arasawa S, Izuta M, et al. Prediction of embolization area after conventional transcatheter arterial chemoembolization for hepatocellular carcinoma using SYNAPSE VINCENT. Dig Dis. 2016;34(6):696–701. https://doi.org/10.1159/000448859 Epub 2016/10/18.CrossRefPubMed

17.

Yamada A, Hara T, Li F, Fujinaga Y, Ueda K, Kadoya M, et al. Quantitative evaluation of liver function with use of gadoxetate disodium-enhanced MR imaging. Radiology. 2011;260(3):727–733. https://doi.org/10.1148/radiol.11100586 Epub 2011/06/30.CrossRefPubMed

18.

Hoekstra LT, de Graaf W, Nibourg GA, Heger M, Bennink RJ, Stieger B, et al. Physiological and biochemical basis of clinical liver function tests: a review. Ann Surg. 2013;257(1):27–36. https://doi.org/10.1097/sla.0b013e31825d5d47 Epub 2012/07/28.CrossRefPubMed

19.

Van Beers BE, Pastor CM, Hussain HK. Primovist, eovist: what to expect? J Hepatol. 2012;57(2):421–429. https://doi.org/10.1016/j.jhep.2012.01.031 Epub 2012/04/17.CrossRefPubMed

20.

Watanabe H, Kanematsu M, Goshima S, Kondo H, Onozuka M, Moriyama N, et al. Staging hepatic fibrosis: comparison of gadoxetate disodium-enhanced and diffusion-weighted MR imaging—preliminary observations. Radiology. 2011;259(1):142–150. https://doi.org/10.1148/radiol.10100621 Epub 2011/01/21.CrossRefPubMed

21.

Nojiri S, Kusakabe A, Fujiwara K, Shinkai N, Matsuura K, Iio E, et al. Noninvasive evaluation of hepatic fibrosis in hepatitis C virus-infected patients using ethoxybenzyl-magnetic resonance imaging. J Gastroenterol Hepatol. 2013;28(6):1032–1039. https://doi.org/10.1111/jgh.12181 Epub 2013/02/26.CrossRefPubMed

22.

Shimamoto D, Nishie A, Asayama Y, Ushijima Y, Takayama Y, Fujita N, et al. MR prediction of liver function and pathology using Gd-EOB-DTPA: effect of liver volume consideration. Biomed Res Int. 2015;2015:141853. https://doi.org/10.1155/2015/141853 Epub 2015/11/27.CrossRefPubMedPubMedCentral

23.

Franca M, Alberich-Bayarri A, Marti-Bonmati L, Oliveira P, Costa FE, Porto G, et al. Accurate simultaneous quantification of liver steatosis and iron overload in diffuse liver diseases with MRI. Abdom radiol (New York). 2017;42(5):1434–1443. https://doi.org/10.1007/s00261-017-1048-0 Epub 2017/01/23.CrossRef

24.

Szurowska E, Sikorska K, Izycka-Swieszewska E, Nowicki T, Romanowski T, Bielawski KP, et al. The role of MR imaging in detection of hepatic iron overload in patients with cirrhosis of different origins. BMC Gastroenterol. 2010;10:13. https://doi.org/10.1186/1471-230x-10-13 Epub 2010/01/29.CrossRefPubMedPubMedCentral

25.

Ludwig J, Batts KP, Moyer TP, Baldus WP, Fairbanks VF. Liver biopsy diagnosis of homozygous hemochromatosis: a diagnostic algorithm. Mayo Clin Proc. 1993;68(3):263–267 Epub 1993/03/01.CrossRefPubMed

26.

Geisel D, Raabe P, Ludemann L, Malinowski M, Stockmann M, Seehofer D, et al. Gd-EOB-DTPA-enhanced MRI for monitoring future liver remnant function after portal vein embolization and extended hemihepatectomy: a prospective trial. Eur Radiol. 2016;27(7):3080–3087. https://doi.org/10.1007/s00330-016-4674-y Epub 2016/12/15.CrossRefPubMed

Title: Evaluation of liver function using gadolinium-ethoxybenzyl-diethylenetriamine pentaacetic acid enhanced magnetic resonance imaging based on a three-dimensional volumetric analysis system
Authors: Masashi Kudo
Naoto Gotohda
Motokazu Sugimoto
Tatsushi Kobayashi
Motohiro Kojima
Shinichiro Takahashi
Masaru Konishi
Ryuichi Hayashi
Publication date: 01-07-2018
Publisher: Springer India
Published in: Hepatology International / Issue 4/2018
Print ISSN: 1936-0533
Electronic ISSN: 1936-0541
DOI: https://doi.org/10.1007/s12072-018-9874-x

Live Webinar | 27-06-2024 | 18:00 (CEST)

Keynote webinar | Spotlight on medication adherence

Reserve your place

Live: Thursday 27th June 2024, 18:00-19:30 (CEST)

WHO estimates that half of all patients worldwide are non-adherent to their prescribed medication. The consequences of poor adherence can be catastrophic, on both the individual and population level.

Join our expert panel to discover why you need to understand the drivers of non-adherence in your patients, and how you can optimize medication adherence in your clinics to drastically improve patient outcomes.

Prof. Kevin Dolgin

Prof. Florian Limbourg

Prof. Anoop Chauhan

Developed by: Springer Medicine

Obesity Clinical Trial Summary

At a glance: The STEP trials

A round-up of the STEP phase 3 clinical trials evaluating semaglutide for weight loss in people with overweight or obesity.

Developed by: Springer Medicine

Keynote webinar | Spotlight on medication adherence

Springer Medicine

Abstract

Background

Methods

Results

Conclusion

Please log in to get access to this content

Other articles of this Issue 4/2018

Linking the gut and liver: crosstalk between regulatory T cells and mucosa-associated invariant T cells

Efficacy and safety of sofosbuvir plus daclatasvir with or without ribavirin: large real-life results of patients with chronic hepatitis C genotype 4

Myosteatosis and sarcopenia are associated with hepatic encephalopathy in patients with cirrhosis

Hepatitis C virus genotype 4-infection and interferon-free treatment in Egypt

Sofosbuvir–velpatasvir plus ribavirin in Japanese patients with genotype 1 or 2 hepatitis C who failed direct-acting antivirals

Sofosbuvir plus Daclatasvir with or without ribavirin for treatment of chronic HCV genotype 4 patients: real-life experience

Keynote webinar | Spotlight on medication adherence

Live: Thursday 27th June 2024, 18:00-19:30 (CEST)

At a glance: The STEP trials