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Utility of Real-time CT/MRI-US Automatic Fusion System Based on Vascular Matching in Percutaneous Radiofrequency Ablation for Hepatocellular Carcinomas: A Prospective Study

Abstract

Purpose

To prospectively evaluate the technical success rate of real-time computed tomography/magnetic resonance imaging and ultrasound (CT/MRI-US) automatic fusion system and the long-term therapeutic efficacy of radiofrequency ablation (RFA) guided by automatic fusion in hepatocellular carcinoma (HCC) patients.

Materials and Methods

139 patients with 151 HCCs were prospectively enrolled for RFA guided by an automatic CT/MRI-US fusion system (PercuNav system, Philips, the Netherlands). Automatic fusion imaging, based on vascular segmentation and registration, was performed by sonographic sweeping at the intercostal plane. The fusion quality, tumor localization confidence and technical feasibility were recorded before and after fusion using a scoring system. Technical success rate of the RFA procedure and local tumor progression (LTP) were assessed during follow-up. Analysis of technical success and LTP was performed using generalized estimating equations and Cox proportional hazard regression analysis.

Results

The success rate of the fusion system was 82.7% (115/139) per patient. The mean sonographic scan time for fusion was 154.4 ± 108.4 s. In patients with successful fusion, the score indicating tumor localization confidence (2.2 ± 0.8 vs. 2.7 ± 0.9) and technical feasibility (2.6 ± 0.8 vs. 3.4 ± 0.7) increased after fusion (p < 0.001). The technical success rate of the RFA procedure was 96.8% (120/124) per tumor in patients with successful fusion, including poorly localized tumors. LTP rates were 8.6%, 12.2% and 15.2% at 1, 2 and 3 years.

Conclusion

The CT/MRI-US automatic fusion system showed a high success rate for image registration and facilitated better feasibility and a high technical success rate of RFA in HCCs, even with poor localization on US.

Level of Evidence

Level 3b, Nonrandomized prospective study

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References

  1. 1.

    Ahn SJ, Lee JM, Lee DH, Lee SM, Yoon JH, Kim YJ, et al. Real-time US-CT/MR fusion imaging for percutaneous radiofrequency ablation of hepatocellular carcinoma. J Hepatol. 2017;66(2):347–54. https://doi.org/10.1016/j.jhep.2016.09.003.

    Article  PubMed  Google Scholar 

  2. 2.

    Kang J, Ryu JK, Son JH, Lee JW, Choi JH, Lee SH, et al. Association between pathologic grade and multiphase computed tomography enhancement in pancreatic neuroendocrine neoplasm. J Gastroenterol Hepatol. 2018. https://doi.org/10.1111/jgh.14139.

    Article  PubMed  Google Scholar 

  3. 3.

    Mauri G, Cova L, De Beni S, Ierace T, Tondolo T, Cerri A, et al. Real-time US-CT/MRI image fusion for guidance of thermal ablation of liver tumors undetectable with US: results in 295 cases. Cardiovasc Intervent Radiol. 2015;38(1):143–51. https://doi.org/10.1007/s00270-014-0897-y.

    Article  PubMed  Google Scholar 

  4. 4.

    Calandri M, Mauri G, Yevich S, Gazzera C, Basile D, Gatti M, et al. Fusion imaging and virtual navigation to guide percutaneous thermal ablation of hepatocellular carcinoma: a review of the literature. Cardiovasc Intervent Radiol. 2019;42(5):639–47. https://doi.org/10.1007/s00270-019-02167-z.

    Article  PubMed  Google Scholar 

  5. 5.

    Lee MW, Rhim H, Cha DI, Kim YJ, Choi D, Kim YS, et al. Percutaneous radiofrequency ablation of hepatocellular carcinoma: fusion imaging guidance for management of lesions with poor conspicuity at conventional sonography. AJR Am J Roentgenol. 2012;198(6):1438–44. https://doi.org/10.2214/AJR.11.7568.

    Article  PubMed  Google Scholar 

  6. 6.

    Song KD, Lee MW, Rhim H, Kang TW, Cha DI, Sinn DH, et al. Percutaneous US/MRI fusion-guided radiofrequency ablation for recurrent subcentimeter hepatocellular carcinoma: technical feasibility and therapeutic outcomes. Radiology. 2018;288(3):878–86. https://doi.org/10.1148/radiol.2018172743.

    Article  PubMed  Google Scholar 

  7. 7.

    Xu ZF, Xie XY, Kuang M, Liu GJ, Chen LD, Zheng YL, et al. Percutaneous radiofrequency ablation of malignant liver tumors with ultrasound and CT fusion imaging guidance. J Clin Ultrasound. 2014;42(6):321–30. https://doi.org/10.1002/jcu.22141.

    Article  PubMed  Google Scholar 

  8. 8.

    Kim AY, Lee MW, Cha DI, Lim HK, Oh YT, Jeong JY, et al. Automatic registration between real-time ultrasonography and pre-procedural magnetic resonance images: a prospective comparison between two registration methods by liver surface and vessel and by liver surface only. Ultrasound Med Biol. 2016;42(7):1627–36. https://doi.org/10.1016/j.ultrasmedbio.2016.02.008.

    Article  PubMed  Google Scholar 

  9. 9.

    Lee MW, Park HJ, Kang TW, Ryu J, Bang WC, Lee B, et al. Image fusion of real-time ultrasonography with computed tomography: factors affecting the registration error and motion of focal hepatic lesions. Ultrasound Med Biol. 2017;43(9):2024–32. https://doi.org/10.1016/j.ultrasmedbio.2017.01.027.

    Article  PubMed  Google Scholar 

  10. 10.

    Ewertsen C, Saftoiu A, Gruionu LG, Karstrup S, Nielsen MB. Real-time image fusion involving diagnostic ultrasound. AJR Am J Roentgenol. 2013;200(3):W249-55. https://doi.org/10.2214/AJR.12.8904.

    Article  PubMed  Google Scholar 

  11. 11.

    Nam WH, Kang DG, Lee D, Lee JY, Ra JB. Automatic registration between 3D intra-operative ultrasound and pre-operative CT images of the liver based on robust edge matching. Phys Med Biol. 2012;57(1):69–91. https://doi.org/10.1088/0031-9155/57/1/69.

    Article  PubMed  Google Scholar 

  12. 12.

    Penney GP, Blackall JM, Hamady MS, Sabharwal T, Adam A, Hawkes DJ. Registration of freehand 3D ultrasound and magnetic resonance liver images. Med Image Anal. 2004;8(1):81–91. https://doi.org/10.1016/j.media.2003.07.003.

    CAS  Article  PubMed  Google Scholar 

  13. 13.

    Wein W, Brunke S, Khamene A, Callstrom MR, Navab N. Automatic CT-ultrasound registration for diagnostic imaging and image-guided intervention. Med Image Anal. 2008;12(5):577–85. https://doi.org/10.1016/j.media.2008.06.006.

    Article  PubMed  Google Scholar 

  14. 14.

    Ahmed M, Solbiati L, Brace CL, Breen DJ, Callstrom MR, Charboneau JW, et al. Image-guided tumor ablation: standardization of terminology and reporting criteria–a 10-year update. J Vasc Interv Radiol. 2014;25(11):1691-705.e4. https://doi.org/10.1016/j.jvir.2014.08.027.

    Article  PubMed  PubMed Central  Google Scholar 

  15. 15.

    Ahn SJ, Lee JM, Chang W, Lee SM, Kang HJ, Yang HK, et al. Clinical utility of real-time ultrasound-multimodality fusion guidance for percutaneous biopsy of focal liver lesions. Eur J Radiol. 2018;103:76–83. https://doi.org/10.1016/j.ejrad.2018.04.002.

    Article  PubMed  Google Scholar 

  16. 16.

    Appelbaum L, Solbiati L, Sosna J, Nissenbaum Y, Greenbaum N, Goldberg SN. Evaluation of an electromagnetic image-fusion navigation system for biopsy of small lesions: assessment of accuracy in an in vivo swine model. Acad Radiol. 2013;20(2):209–17. https://doi.org/10.1016/j.acra.2012.09.020.

    Article  PubMed  Google Scholar 

  17. 17.

    Krucker J, Xu S, Glossop N, Viswanathan A, Borgert J, Schulz H, et al. Electromagnetic tracking for thermal ablation and biopsy guidance: clinical evaluation of spatial accuracy. J Vasc Interv Radiol. 2007;18(9):1141–50. https://doi.org/10.1016/j.jvir.2007.06.014.

    Article  PubMed  PubMed Central  Google Scholar 

  18. 18.

    Cha DI, Lee MW, Kim AY, Kang TW, Oh YT, Jeong JY, et al. Automatic image fusion of real-time ultrasound with computed tomography images: a prospective comparison between two auto-registration methods. Acta Radiol. 2017;58(11):1349–57. https://doi.org/10.1177/0284185117693459.

    Article  PubMed  Google Scholar 

  19. 19.

    Yoon JH, Lee JM, Klotz E, Woo H, Yu MH, Joo I, et al. Prediction of local tumor progression after radiofrequency ablation (RFA) of hepatocellular carcinoma by assessment of ablative margin using Pre-RFA MRI and Post-RFA CT registration. Korean J Radiol. 2018;19(6):1053–65. https://doi.org/10.3348/kjr.2018.19.6.1053.

    Article  PubMed  PubMed Central  Google Scholar 

  20. 20.

    Au KP, Chiang CL, Chan ACY, Cheung TT, Lo CM, Chok KSH. Initial experience with stereotactic body radiotherapy for intrahepatic hepatocellular carcinoma recurrence after liver transplantation. World J Clin Cases. 2020;8(13):2758–68. https://doi.org/10.12998/wjcc.v8.i13.2758.

    Article  PubMed  PubMed Central  Google Scholar 

  21. 21.

    Baek MY, Yoo JJ, Jeong SW, Jang JY, Kim YK, Jeong SO, et al. Clinical outcomes of patients with a single hepatocellular carcinoma less than 5 cm treated with transarterial chemoembolization. Korean J Intern Med. 2019;34(6):1223–32. https://doi.org/10.3904/kjim.2018.058.

    Article  PubMed  Google Scholar 

  22. 22.

    Iwazawa J, Ohue S, Hashimoto N, Mitani T. Local tumor progression following lipiodol-based targeted chemoembolization of hepatocellular carcinoma: a retrospective comparison of miriplatin and epirubicin. Cancer Manag Res. 2012;4:113–9. https://doi.org/10.2147/cmar.S30431.

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  23. 23.

    Zheng L, Li HL, Guo CY, Luo SX. Comparison of the efficacy and prognostic factors of transarterial chemoembolization plus microwave ablation versus transarterial chemoembolization alone in patients with a large solitary or multinodular hepatocellular carcinomas. Korean J Radiol. 2018;19(2):237–46. https://doi.org/10.3348/kjr.2018.19.2.237.

    Article  PubMed  PubMed Central  Google Scholar 

  24. 24.

    Wigg AJ, Narayana SK, Le H, Iankov I, Chinnaratha MA, Tse E, et al. Stereotactic body radiation therapy for early hepatocellular carcinoma: a retrospective analysis of the South Australian experience. ANZ J Surg. 2019;89(9):1138–43. https://doi.org/10.1111/ans.15130.

    Article  PubMed  Google Scholar 

  25. 25.

    Kong WT, Zhang WW, Qiu YD, Zhou T, Qiu JL, Zhang W, et al. Major complications after radiofrequency ablation for liver tumors: analysis of 255 patients. World J Gastroenterol. 2009;15(21):2651–6. https://doi.org/10.3748/wjg.15.2651.

    Article  PubMed  PubMed Central  Google Scholar 

  26. 26.

    Schullian P, Johnston E, Laimer G, Putzer D, Eberle G, Amann A, et al. Frequency and risk factors for major complications after stereotactic radiofrequency ablation of liver tumors in 1235 ablation sessions: a 15-year experience. Eur Radiol. 2020. https://doi.org/10.1007/s00330-020-07409-0.

    Article  PubMed  PubMed Central  Google Scholar 

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Acknowledgements

This study was conducted under technical support from Philips (Best, the Netherlands) and statistical support from Medical Research Collaborating Center (MRCC) of Seoul National University Hospital

Funding

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Correspondence to Jeong Min Lee.

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The authors declare that they have no conflict of interest.

Ethical approval

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.

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Informed consent was obtained from all individual participants included in the study.

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Appendices

Appendix 1

See Table

Table 7 Contraindications for RFA in our institute

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Appendix 2

See Table

Table 8 Comparison between patients with success and failure in automatic fusion process

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Appendix 3

See Table

Table 9 Results from pre-procedural planning session in entire enrolled patients

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Appendix 4

See Table

Table 10 Analysis for technical success/efficacy per tumor

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Appendix 5

See Table

Table 11 Risk factor analysis for local tumor progression per tumor in entire enrolled patients

11

Appendix 6

See Table

Table 12 Comparison of baseline characteristics between subgroups of tumors regarding localization confidence*

12

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Han, S., Lee, J.M., Lee, D.H. et al. Utility of Real-time CT/MRI-US Automatic Fusion System Based on Vascular Matching in Percutaneous Radiofrequency Ablation for Hepatocellular Carcinomas: A Prospective Study. Cardiovasc Intervent Radiol 44, 1579–1596 (2021). https://doi.org/10.1007/s00270-021-02896-0

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Keywords

  • Hepatocellular carcinoma
  • Radiofrequency ablation
  • CT
  • MRI-US automatic fusion system