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Eur Radiol. 2016 Oct;26(10):3437-46. doi: 10.1007/s00330-015-4190-5. Epub 2016 Jan 8.

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

Author information

1
Department of Radiology and Center for Imaging Science, Samsung Medical Center, Sungkyunkwan University School of Medicine, 50 Irwon-Dong, Gangnam-gu, Seoul, 135-710, Korea.
2
Department of Radiology and Center for Imaging Science, Samsung Medical Center, Sungkyunkwan University School of Medicine, 50 Irwon-Dong, Gangnam-gu, Seoul, 135-710, Korea. rhimhc@skku.edu.
3
Division of Hepatology, Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, 135-710, Republic of Korea.
4
Biostatics and Clinical Epidemiology Center, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, 135-710, Republic of Korea.

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:

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

PMID:
26747262
DOI:
10.1007/s00330-015-4190-5
[Indexed for MEDLINE]

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