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Updated: Dec 6, 2025

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Published on: March 3, 2023
Virtual navigation-guided radiofrequency ablation for recurrent hepatocellular carcinoma invisible on ultrasound
Qi-Yu Zhao1, Li-Ting Xie1, Shuo-Chun Chen1
1Department of Ultrasound, First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 310003, China.
Background:
No reports are available on the technical efficiency and therapeutic response of virtual navigation (VN)-guided radiofrequency ablation (RFA) for patients with recurrent hepatocellular carcinoma (HCC) after hepatic resection. The aim of this study was to investigate the overall technical performance and outcome of VN-guided RFA in recurrent HCC patients. In addition, a nomogram model was developed to predict the factors influencing the overall survival (OS).
Methods:
This was a prospective study on 76 recurrent HCC patients who underwent VN-guided RFA between June 2015 and February 2018. The technical feasibility, success, and efficiency, OS, local tumor progression, and complications were evaluated. A multivariate Cox regression analysis was conducted to predict the significant factors, and a nomogram including independent predictive factors was subsequently plotted to predict OS.
Results:
The technical feasibility, success, and efficiency rates of VN-guided RFA were 86.4%, 94.7%, and 97.4%, respectively. The cumulative OS rates at 1-, 2-, and 3-year were 88.1%, 79.7%, and 71.0%, respectively. The cumulative local tumor progression rates at 1-, 2-, and 3-year were 5.5%, 8.7%, and 14.0%, respectively. In addition, the minor and major complication rates were 5.3% and 3.9%, respectively. No intervention-related deaths occurred during the follow-up period. The C-index of the OS nomogram in this study was 0.737.
Conclusions:
VN-guided RFA is an effective therapeutic option in recurrent HCC patients and improves the long-term outcomes especially for the lesions that cannot be detected in the two-dimensional ultrasound. Besides, the nomogram may be a useful supporting tool in predicting OS to estimate the individual survival probability, optimize treatment options, and facilitate decision-making.
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