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The value of contrast-enhanced portal vein imaging at the hepatobiliary phase obtained with gadobenate dimeglumine for predicting decompensation and transplant-free survival in chronic liver disease

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Abstract

Objectives

To investigate the value of contrast-enhanced portal vein imaging at the hepatobiliary phase obtained with gadobenate dimeglumine for predicting clinical outcomes in patients with chronic liver disease (CLD).

Methods

Three hundred and fourteen CLD patients who underwent gadobenate dimeglumine–enhanced hepatic magnetic resonance imaging were stratified into three groups: nonadvanced CLD (n = 116), compensated advanced CLD (n = 120), and decompensated advanced CLD (n = 78) groups. The liver-to-portal vein contrast ratio (LPC) and liver-spleen contrast ratio (LSC) at the hepatobiliary phase were measured. The value of LPC for predicting hepatic decompensation and transplant-free survival was assessed using Cox regression analysis and Kaplan–Meier analysis.

Results

The diagnostic performance of LPC was significantly better than LSC in evaluating the severity of CLD. During a median follow-up period of 53.0 months, the LPC was a significant predictor for hepatic decompensation (p < 0.001) in patients with compensated advanced CLD. The predictive performance of LPC was higher than that of the model for end-stage liver disease score (p = 0.006). With the optimal cut-off value, patients with LPC ≤ 0.98 had a higher cumulative incidence of hepatic decompensation than patients with LPC > 0.98 (p < 0.001). The LPC was also a significant predictive factor for transplant-free survival in patients with compensated advanced CLD (p = 0.007) and those with decompensated advanced CLD (p = 0.002).

Conclusions

Contrast-enhanced portal vein imaging at the hepatobiliary phase obtained with gadobenate dimeglumine is a valuable imaging biomarker for predicting hepatic decompensation and transplant-free survival in CLD patients.

Key Points

• The liver-to-portal vein contrast ratio (LPC) significantly outperformed liver-spleen contrast ratio in evaluating the severity of chronic liver disease.

• The LPC was a significant predictor for hepatic decompensation in patients with compensated advanced chronic liver disease.

• The LPC was a significant predictor for transplant-free survival in patients with compensated and those with decompensated advanced chronic liver disease.

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Abbreviations

ALT:

Alanine aminotransferase

AST:

Aspartate aminotransferase

AUC:

Area under the curve

CI:

Confidence interval

CLD:

Chronic liver disease

eGFR:

Estimated glomerular filtration rate

FIB-4:

Fibrosis-4 score

HCC:

Hepatocellular carcinoma

HR:

Hazard ratio

HUI:

Hepatic uptake index

LMR:

Liver-muscle-ratio

LPC:

Liver-to-portal vein contrast ratio

LSC:

Liver-spleen contrast ratio

MELD:

Model for end-stage liver disease

MRI:

Magnetic resonance imaging

OATP:

Organic anion transporting polypeptides

PLT:

Platelet count

RLE:

Relative liver enhancement

ROC:

Receiver operating characteristic

ROI:

Region of interest

SI:

Signal intensity

References

  1. Gidener T, Yin M, Dierkhising RA et al (2022) Magnetic resonance elastography for prediction of long-term progression and outcome in chronic liver disease: a retrospective study. Hepatology 75:379–390

    Article  PubMed  Google Scholar 

  2. Garcia-Tsao G, Friedman S, Iredale J, Pinzani M (2010) Now there are many (stages) where before there was one: in search of a pathophysiological classification of cirrhosis. Hepatology 51:1445–1449

    Article  PubMed  Google Scholar 

  3. Yoon JH, Lee JM, Kim E, Okuaki T, Han JK (2017) Quantitative liver function analysis: volumetric T1 mapping with fast multisection B1 inhomogeneity correction in hepatocyte-specific contrast-enhanced liver MR imaging. Radiology 282:408–417

    Article  PubMed  Google Scholar 

  4. D’amico G, Garcia-Tsao G, Pagliaro L (2006) Natural history and prognostic indicators of survival in cirrhosis: a systematic review of 118 studies. J Hepatol 44:217–231

    Article  PubMed  Google Scholar 

  5. Rainer F, Horvath A, Sandahl TD et al (2018) Soluble CD163 and soluble mannose receptor predict survival and decompensation in patients with liver cirrhosis, and correlate with gut permeability and bacterial translocation. Aliment Pharmacol Ther 47:657–664

    Article  CAS  PubMed  Google Scholar 

  6. Durand F, Valla D (2005) Assessment of the prognosis of cirrhosis: Child-Pugh versus MELD. J Hepatol 42:S100–S107

    Article  PubMed  Google Scholar 

  7. Ripoll C, Groszmann R, Garcia-Tsao G et al (2007) Hepatic venous pressure gradient predicts clinical decompensation in patients with compensated cirrhosis. Gastroenterology 133:481–488

    Article  CAS  PubMed  Google Scholar 

  8. Singh S, Muir AJ, Dieterich DT, Falck-Ytter YT (2017) American Gastroenterological Association Institute technical review on the role of elastography in chronic liver diseases. Gastroenterology 152:1544–1577

    Article  PubMed  Google Scholar 

  9. Shen Y, Wu SD, Wu L et al (2019) The prognostic role of liver stiffness in patients with chronic liver disease: a systematic review and dose-response meta-analysis. Hepatol Int 13:560–572

    Article  PubMed  Google Scholar 

  10. Friedrich-Rust M, Poynard T, Castera L (2016) Critical comparison of elastography methods to assess chronic liver disease. Nat Rev Gastroenterol Hepatol 13:402–411

    Article  PubMed  Google Scholar 

  11. Kupczyk PA, Mesropyan N, Isaak A et al (2021) Quantitative MRI of the liver: Evaluation of extracellular volume fraction and other quantitative parameters in comparison to MR elastography for the assessment of hepatopathy. Magn Reson Imaging 77:7–13

    Article  CAS  PubMed  Google Scholar 

  12. Luetkens JA, Klein S, Träber F et al (2018) Quantification of liver fibrosis at T1 and T2 mapping with extracellular volume fraction mri: preclinical results. Radiology 288:748–754

    Article  PubMed  Google Scholar 

  13. Van Beers BE, Pastor CM, Hussain HK (2012) Primovist, Eovist: what to expect? J Hepatol 57:421–429

    Article  PubMed  Google Scholar 

  14. Fidler J, Hough D (2011) Hepatocyte-specific magnetic resonance imaging contrast agents. Hepatology 53:678–682

    Article  PubMed  Google Scholar 

  15. Bonatti M, Valletta R, Avesani G et al (2021) Liver enhancement during hepatobiliary phase after Gd-BOPTA administration: correlation with liver and renal function. Eur Radiol 31:2490–2496

    Article  CAS  PubMed  Google Scholar 

  16. Sandrasegaran K, Cui E, Elkady R et al (2018) Can functional parameters from hepatobiliary phase of gadoxetate MRI predict clinical outcomes in patients with cirrhosis? Eur Radiol 28:4215–4224

    Article  PubMed  Google Scholar 

  17. Liu C, Shen Z, Ma H et al (2022) Gd-BOPTA-enhanced hepatobiliary phase MR imaging can predict the prognosis of patients with acute-on-chronic liver failure. Eur Radiol 32:3006–3015

    Article  CAS  PubMed  Google Scholar 

  18. Lee NK, Kim S, Kim GH et al (2012) Significance of the “delayed hyperintense portal vein sign” in the hepatobiliary phase MRI obtained with Gd-EOB-DTPA. J Magn Reson Imaging 36:678–685

    Article  PubMed  Google Scholar 

  19. Zhang W, Wang X, Miao Y, Hu C, Zhao W (2018) Liver function correlates with liver-to-portal vein contrast ratio during the hepatobiliary phase with Gd-EOB-DTPA-enhanced MR at 3 Tesla. Abdom Radiol (NY) 43:2262–2269

    Article  PubMed  Google Scholar 

  20. Yang M, Zhang Y, Zhao W, Cheng W, Wang H, Guo S (2020) Evaluation of liver function using liver parenchyma, spleen and portal vein signal intensities during the hepatobiliary phase in Gd-EOB-DTPA-enhanced MRI. BMC Med Imaging 20:119

    Article  PubMed  PubMed Central  Google Scholar 

  21. Takatsu Y, Kobayashi S, Miyati T, Shiozaki T (2016) A novel method for evaluating enhancement using gadolinium-ethoxybenzyl-diethylenetriamine penta-acetic acid in the hepatobiliary phase of magnetic resonance imaging. Clin Imaging 40:1112–1117

    Article  PubMed  Google Scholar 

  22. Cai S, Lin X, Sun Y et al (2022) Quantitative parameters obtained from gadobenate dimeglumine-enhanced MRI at the hepatobiliary phase can predict post-hepatectomy liver failure and overall survival in patients with hepatocellular carcinoma. Eur J Radiol 154:110449

    Article  PubMed  Google Scholar 

  23. Liu C, Sun Y, Yang Y et al (2021) Gadobenate dimeglumine-enhanced biliary imaging from the hepatobiliary phase can predict progression in patients with liver cirrhosis. Eur Radiol 31:5840–5850

    Article  CAS  PubMed  Google Scholar 

  24. Sterling RK, Lissen E, Clumeck N et al (2006) Development of a simple noninvasive index to predict significant fibrosis in patients with HIV/HCV coinfection. Hepatology 43:1317–1325

    Article  CAS  PubMed  Google Scholar 

  25. Bastati N, Beer L, Mandorfer M et al (2020) Does the functional liver imaging score derived from gadoxetic acid-enhanced MRI predict outcomes in chronic liver disease? Radiology 294:98–107

    Article  PubMed  Google Scholar 

  26. de Franchis R, Faculty BVI (2015) Expanding consensus in portal hypertension: report of the Baveno VI Consensus Workshop: stratifying risk and individualizing care for portal hypertension. J Hepatol 63:743–752

    Article  PubMed  Google Scholar 

  27. Okada M, Murakami T, Kuwatsuru R et al (2016) 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 281:474–483

    Article  PubMed  Google Scholar 

  28. Wibmer A, Prusa AM, Nolz R, Gruenberger T, Schindl M, Ba-Ssalamah A (2013) Liver failure after major liver resection: risk assessment by using preoperative Gadoxetic acid-enhanced 3-T MR imaging. Radiology 269:777–786

    Article  PubMed  Google Scholar 

  29. Yamada A, Hara T, Li F et al (2011) Quantitative evaluation of liver function with use of gadoxetate disodium-enhanced MR imaging. Radiology 260:727–733

    Article  PubMed  Google Scholar 

  30. Obmann VC, Marx C, Berzigotti A et al (2019) Liver MRI susceptibility-weighted imaging (SWI) compared to T2* mapping in the presence of steatosis and fibrosis. Eur J Radiol 118:66–74

    Article  PubMed  Google Scholar 

  31. Tsuda N, Matsui O (2010) Cirrhotic rat liver: reference to transporter activity and morphologic changes in bile canaliculi–gadoxetic acid-enhanced MR imaging. Radiology 256:767–773

    Article  PubMed  Google Scholar 

  32. Feier D, Balassy C, Bastati N et al (2013) Liver fibrosis: histopathologic and biochemical influences on diagnostic efficacy of hepatobiliary contrast-enhanced MR imaging in staging. Radiology 269:460–468

    Article  PubMed  Google Scholar 

  33. Pedersen M (2007) Safety update on the possible causal relationship between gadolinium-containing MRI agents and nephrogenic systemic fibrosis. J Magn Reson Imaging 25:881–883

    Article  PubMed  Google Scholar 

  34. Perazella MA, Rodby RA (2007) Gadolinium use in patients with kidney disease: a cause for concern. Semin Dial 20:179–185

    Article  PubMed  Google Scholar 

  35. Schneider ARP, Schneider CV, Schneider KM et al (2022) Early prediction of decompensation (EPOD) score: Non-invasive determination of cirrhosis decompensation risk. Liver Int 42:640–650

    Article  PubMed  Google Scholar 

  36. Johnson PJ, Berhane S, Kagebayashi C et al (2015) Assessment of liver function in patients with hepatocellular carcinoma: a new evidence-based approach-the ALBI grade. J Clin Oncol 33:550–558

    Article  PubMed  Google Scholar 

  37. Tanimoto A, Lee JM, Murakami T, Huppertz A, Kudo M, Grazioli L (2009) Consensus report of the 2nd International Forum for Liver MRI. Eur Radiol 19:S975–S989

    Article  PubMed  Google Scholar 

  38. Allen BC, Ho LM, Jaffe TA, Miller CM, Mazurowski MA, Bashir MR (2018) Comparison of visualization rates of LI-RADS Version 2014 major features with IV gadobenate dimeglumine or gadoxetate disodium in patients at risk for hepatocellular carcinoma. AJR Am J Roentgenol 210:1266–1272

    Article  PubMed  Google Scholar 

  39. Rong D, He B, Tang W et al (2022) Comparison of gadobenate-enhanced mri and gadoxetate-enhanced mri for hepatocellular carcinoma detection using LI-RADS version 2018: a prospective intraindividual randomized study. AJR Am J Roentgenol 218:687–698

    Article  PubMed  Google Scholar 

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Funding

This research was supported by the Natural Science Foundation of Shandong Province (ZR2020MH285).

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Authors and Affiliations

  1. Department of Radiology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong Province, 250021, China

    Shuo Cai, Yongqing Yang, Wenjing Ma, Yu Wang, Xiangtao Lin, Ximing Wang & Xinya Zhao

  2. Department of Medical Imaging, Shandong Public Health Clinical Center, Jinan, Shandong Province, 250021, China

    Nan Lin

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  1. Shuo Cai
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Correspondence to Ximing Wang or Xinya Zhao.

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The scientific guarantor of this publication is Prof. Xinya Zhao.

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The authors of this manuscript declare no relationships with any companies, whose products or services may be related to the subject matter of the article.

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Cai, S., Lin, N., Yang, Y. et al. The value of contrast-enhanced portal vein imaging at the hepatobiliary phase obtained with gadobenate dimeglumine for predicting decompensation and transplant-free survival in chronic liver disease. Eur Radiol 33, 3425–3434 (2023). https://doi.org/10.1007/s00330-023-09489-0

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