European Radiology

, Volume 26, Issue 10, pp 3437–3446 | Cite as

Magnetic resonance imaging with gadoxetic acid for local tumour progression after radiofrequency ablation in patients with hepatocellular carcinoma

  • Tae Wook Kang
  • Hyunchul Rhim
  • Jisun Lee
  • Kyoung Doo Song
  • Min Woo Lee
  • Young-sun Kim
  • Hyo Keun Lim
  • Kyung Mi Jang
  • Seong Hyun Kim
  • Geum-Youn Gwak
  • Sin-Ho Jung
Vascular-Interventional

Abstract

Objectives

To develop and validate a prediction model using magnetic resonance imaging (MRI) for local tumour progression (LTP) after radiofrequency ablation (RFA) in hepatocellular carcinoma (HCC) patients.

Methods

Two hundred and eleven patients who had received RFA as first-line treatment for HCC were retrospectively analyzed. They had undergone gadoxetic acid-enhanced MRI before treatment, and parameters including tumour size; margins; signal intensities on T1-, T2-, and diffusion-weighted images, and hepatobiliary phase images (HBPI); intratumoral fat or tumoral capsules; and peritumoural hypointensity in the HBPI were used to develop a prediction model for LTP after treatment. This model to discriminate low-risk from high-risk LTP groups was constructed based on Cox regression analysis.

Results

Our analyses produced the following model: ‘risk score = 0.617 × tumour size + 0.965 × tumour margin + 0.867 × peritumoural hypointensity on HBPI’. This was able to predict which patients were at high risk for LTP after RFA (p < 0.001). Patients in the low-risk group had a significantly better 5-year LTP-free survival rate compared to the high-risk group (89.6 % vs. 65.1 %; hazard ratio, 3.60; p < 0.001).

Conclusion

A predictive model based on MRI before RFA could robustly identify HCC patients at high risk for LTP after treatment.

Key points

Tumour size, margin, and peritumoural hypointensity on HBPI were risk factors for LTP.

The risk score model can predict which patients are at high risk for LTP.

This prediction model could be helpful for risk stratification of HCC patients.

Keywords

Radiofreqeuncy ablation Hepatocellular carcinoma Magnetic resonance imaging Prediction model Local tumour progression 

Abbreviations

RFA

radiofrequency ablation

HCC

hepatocellular carcinoma

LTP

local tumour progression

MRI

magnetic resonance imaging

US

ultrasound

CT

computed tomography

DWI

diffusion-weighted image

HBPI

hepatobiliary phase images

HR

hazard ratio

CI

confidence interval

Notes

Acknowledgments

The scientific guarantor of this publication is Won Jae Lee. 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. The authors state that this work has not received any funding. One of the authors (Sin-Ho Jung) has significant statistical expertise. Institutional Review Board approval was obtained. Written informed consent was waived by the Institutional Review Board. This is the first study using this kind of cohort. Methodology: retrospective, prognostic study / observational, performed at one institution.

Supplementary material

330_2015_4190_MOESM1_ESM.doc (66 kb)
ESM 1 (DOC 66 kb)

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Copyright information

© European Society of Radiology 2016

Authors and Affiliations

  • Tae Wook Kang
    • 1
  • Hyunchul Rhim
    • 1
  • Jisun Lee
    • 1
  • Kyoung Doo Song
    • 1
  • Min Woo Lee
    • 1
  • Young-sun Kim
    • 1
  • Hyo Keun Lim
    • 1
  • Kyung Mi Jang
    • 1
  • Seong Hyun Kim
    • 1
  • Geum-Youn Gwak
    • 2
  • Sin-Ho Jung
    • 3
  1. 1.Department of Radiology and Center for Imaging Science, Samsung Medical CenterSungkyunkwan University School of MedicineSeoulKorea
  2. 2.Division of Hepatology, Department of Medicine, Samsung Medical CenterSungkyunkwan University School of MedicineSeoulRepublic of Korea
  3. 3.Biostatics and Clinical Epidemiology Center, Samsung Medical CenterSungkyunkwan University School of MedicineSeoulRepublic of Korea

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