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Comparison Between CT and MR Images as More Favorable Reference Data Sets for Fusion Imaging-Guided Radiofrequency Ablation or Biopsy of Hepatic Lesions: A Prospective Study with Focus on Patient’s Respiration

  • Clinical Investigation
  • Published:
CardioVascular and Interventional Radiology Aims and scope Submit manuscript

Abstract

Purpose

To identify the more accurate reference data sets for fusion imaging-guided radiofrequency ablation or biopsy of hepatic lesions between computed tomography (CT) and magnetic resonance (MR) images.

Materials and Methods

This study was approved by the institutional review board, and written informed consent was received from all patients. Twelve consecutive patients who were referred to assess the feasibility of radiofrequency ablation or biopsy were enrolled. Automatic registration using CT and MR images was performed in each patient. Registration errors during optimal and opposite respiratory phases, time required for image fusion and number of point locks used were compared using the Wilcoxon signed-rank test.

Results

The registration errors during optimal respiratory phase were not significantly different between image fusion using CT and MR images as reference data sets (p = 0.969). During opposite respiratory phase, the registration error was smaller with MR images than CT (p = 0.028). The time and the number of points locks needed for complete image fusion were not significantly different between CT and MR images (p = 0.328 and p = 0.317, respectively).

Conclusion

MR images would be more suitable as the reference data set for fusion imaging-guided procedures of focal hepatic lesions than CT images.

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References

  1. Lee MW, Rhim H, Cha DI, 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.

    Article  PubMed  Google Scholar 

  2. Hirooka M, Iuchi H, Kumagi T, et al. Virtual sonographic radiofrequency ablation of hepatocellular carcinoma visualized on CT but not on conventional sonography. Am J Roentgenol. 2006;186(5_supplement):S255–60.

    Article  Google Scholar 

  3. Lee MW, Rhim H, Cha DI, Kim YJ, Lim HK. Planning US for percutaneous radiofrequency ablation of small hepatocellular carcinomas (1–3 cm): value of fusion imaging with conventional US and CT/MR images. J Vasc Interv Radiol. 2013;24(7):958–65.

    Article  PubMed  Google Scholar 

  4. Liu FY, Yu XL, Liang P, et al. Microwave ablation assisted by a real-time virtual navigation system for hepatocellular carcinoma undetectable by conventional ultrasonography. Eur J Radiol. 2012;81(7):1455–9.

    Article  PubMed  Google Scholar 

  5. Mauri G, Cova L, De Beni S, 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.

    Article  PubMed  Google Scholar 

  6. Goldberg SN, Grassi CJ, Cardella JF, et al. Image-guided tumor ablation: standardization of terminology and reporting criteria. J Vasc Interv Radiol. 2009;20(7 Suppl):S377–90.

    Article  PubMed  Google Scholar 

  7. Ahmed M, Brace CL, Lee FT Jr, Goldberg SN. Principles of and advances in percutaneous ablation. Radiology. 2011;258(2):351–69.

    Article  PubMed  Google Scholar 

  8. Kim JE, Kim YS, Rhim H, et al. Outcomes of patients with hepatocellular carcinoma referred for percutaneous radiofrequency ablation at a tertiary center: analysis focused on the feasibility with the use of ultrasonography guidance. Eur J Radiol. 2011;79(2):e80–4.

    Article  PubMed  Google Scholar 

  9. Cha DI, Lee MW, Kim YK, et al. Assessing patients with hepatocellular carcinoma meeting the Milan criteria: is liver 3 tesla MR with gadoxetic acid necessary in addition to liver CT? J Magn Reson Imaging. 2014;39(4):842–52.

    Article  PubMed  Google Scholar 

  10. Kim SH, Kim SH, Lee J, et al. Gadoxetic acid-enhanced MRI versus triple-phase MDCT for the preoperative detection of hepatocellular carcinoma. AJR Am J Roentgenol. 2009;192(6):1675–81.

    Article  PubMed  Google Scholar 

  11. Lee JY, Choi BI, Chung YE, Kim MW, Kim SH, Han JK. Clinical value of CT/MR-US fusion imaging for radiofrequency ablation of hepatic nodules. Eur J Radiol. 2012;81(9):2281–9.

    Article  PubMed  Google Scholar 

  12. Lee MW. Fusion imaging of real-time ultrasonography with CT or MRI for hepatic intervention. Ultrasonography. 2014;33(4):227–39.

    Article  PubMed  PubMed Central  Google Scholar 

  13. Cha DI, Lee MW, Kim AY, et al. Automatic image fusion of real-time ultrasound with computed tomography images: a prospective comparison between two auto-registration methods. Acta Radiol. 2017. doi:10.1177/0284185117693459.

    Google Scholar 

  14. Cha DI, Lee MW, Song KD, et al. A prospective comparison between auto-registration and manual registration of real-time ultrasound with MR images for percutaneous ablation or biopsy of hepatic lesions. Abdom Radiol. 2017. doi:10.1007/s00261-017-1075-x.

    Google Scholar 

  15. Crocetti L, Lencioni R, DeBeni S, See TC, Della Pina C, Bartolozzi C. Targeting liver lesions for radiofrequency ablation: an experimental feasibility study using a CT–US fusion imaging system. Invest Radiol. 2008;43(1):33–9.

    Article  PubMed  Google Scholar 

  16. Suramo I, Paivansalo M, Myllyla V. Cranio-caudal movements of the liver, pancreas and kidneys in respiration. Acta Radiol Diagn (Stockh). 1984;25(2):129–31.

    Article  CAS  Google Scholar 

  17. Balter JM, Ten Haken RK, Lawrence TS, Lam KL, Robertson JM. Uncertainties in CT-based radiation therapy treatment planning associated with patient breathing. Int J Radiat Oncol Biol Phys. 1996;36(1):167–74.

    Article  CAS  PubMed  Google Scholar 

  18. Shimizu S, Shirato H, Xo B, et al. Three-dimensional movement of a liver tumor detected by high-speed magnetic resonance imaging. Radiother Oncol. 1999;50(3):367–70.

    Article  CAS  PubMed  Google Scholar 

  19. Mauri G, De Beni S, Forzoni L, et al. Virtual navigator automatic registration technology in abdominal application. Conf Proc IEEE Eng Med Biol Soc. 2014;2014:5570–4.

    CAS  PubMed  Google Scholar 

  20. Kadoury S, Wood BJ, Venkatesan AM, Ardon R, Jago J, Kruecker J. Graph-based surface extraction of the liver using locally adaptive priors for multimodal interventional image registration. In: Proc. SPIE 8316, Medical imaging 2012: image-guided procedures, robotic interventions, and modeling. 2012. doi:10.1117/12.911363.

  21. 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.

    Article  PubMed  Google Scholar 

  22. Kunishi Y, Numata K, Morimoto M, et al. Efficacy of fusion imaging combining sonography and hepatobiliary phase MRI with Gd-EOB-DTPA to detect small hepatocellular carcinoma. AJR Am J Roentgenol. 2012;198(1):106–14.

    Article  PubMed  Google Scholar 

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Acknowledgements

This study was supported by a Samsung Medison Grant [#PHO0132251].

Author information

Authors and Affiliations

  1. Department of Radiology and Center for Imaging Science, Samsung Medical Center, Sungkyunkwan University School of Medicine, 81 Irwon-Ro, Gangnam-gu, Seoul, 06351, Republic of Korea

    Dong Ik Cha, Min Woo Lee & Tae Wook Kang

  2. Medical Imaging R&D Group, Health & Medical Equipment Business, Samsung Electronics Co., Ltd., Suwon, Republic of Korea

    Young-Taek Oh, Ja-Yeon Jeong, Jung-Woo Chang, Jiwon Ryu, Kyong Joon Lee, Jaeil Kim & Won-Chul Bang

  3. Infrastructure Technology Lab, R&D Center, Samsung Medison, Seoul, Republic of Korea

    Dong Kuk Shin, Sung Jin Choi & Dalkwon Koh

  4. Biostatistics and Clinical Epidemiology Center, Samsung Medical Center, Seoul, Republic of Korea

    Kyunga Kim

Authors
  1. Dong Ik Cha
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  2. Min Woo Lee
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Corresponding author

Correspondence to Min Woo Lee.

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Conflict of interest

The funder only provided support in the form of salaries for authors who are employees of Samsung Medison. Authors who are employees of Samsung Electronics Co. [Y.O., J.J., J.C., J.R., K.J.L., J.K. and W.C.B.] or Samsung Medison [D.K.S., S.J.C. and D.K.] participated in the development of the S-Fusion, provided technical advices and analysis tools during the clinical trial and contributed in writing the manuscript, especially technical parts. Only the authors from Samsung Medical Center, Department of Radiology, had full control of the study design, data collection, decision to publish or preparation of the manuscript. One author (M.W.L.) is also a consultant for Samsung Medison.

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 Declaration of Helsinki and its later amendments or comparable ethical standards.

Informed Consent

Written informed consent was obtained from all patients for this prospective study.

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Cha, D.I., Lee, M.W., Kang, T.W. et al. Comparison Between CT and MR Images as More Favorable Reference Data Sets for Fusion Imaging-Guided Radiofrequency Ablation or Biopsy of Hepatic Lesions: A Prospective Study with Focus on Patient’s Respiration. Cardiovasc Intervent Radiol 40, 1567–1575 (2017). https://doi.org/10.1007/s00270-017-1666-5

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  • DOI: https://doi.org/10.1007/s00270-017-1666-5

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