Advertisement

CardioVascular and Interventional Radiology

, Volume 42, Issue 1, pp 69–77 | Cite as

Utility of the Virtual Liver Parenchymal Perfusion Area Using a Commercially Available Workstation in Transarterial Chemoembolization for Hepatocellular Carcinoma

  • Mitsuhiro KinoshitaEmail author
  • Katsuya Takechi
  • Yuta Arai
  • Ryozo Shirono
  • Yoshihiro Nagao
  • Shoichi Izumi
  • Takuya Akagawa
  • Shiori Noda
  • Shoichiro Takao
  • Chikara Ogawa
  • Daisuke Suwa
  • Katsuyoshi Tamaki
  • Naoto Uyama
  • Yoko Akagawa
  • Kyosuke Osaki
  • Norio Ohnishi
  • Hayato Tani
Clinical Investigation
  • 126 Downloads

Abstract

Purpose

To evaluate the accuracy of the virtual liver parenchymal perfusion area using a commercially available workstation and liver analysis software in conventional transarterial chemoembolization (cTACE) for hepatocellular carcinoma (HCC).

Materials and Methods

This method was retrospectively applied to 29 treated HCCs in 23 patients. The virtual embolic area (VEA) was estimated based on cone beam computed tomography during hepatic arteriography using a commercially available workstation and liver analysis software by two observer groups (group A: experts; group B: semi-experts). The real embolic area (REA) was defined as the area where iodized oil accumulated on computed tomography at 1 week after cTACE. The REA was estimated by each of the two groups, and the mean REA between the groups (mREA) was used as a standard reference. Agreement of volume and cross-sectional area in three orthogonal planes between the VEA and mREA were analyzed using intraclass correlation coefficients (ICCs) and Bland–Altman plots.

Results

The ICCs for volume between VEA and mREA were 0.97 and 0.88 for groups A and B, respectively, and those for cross-sectional area were 0.94 and 0.88 for the axial plane, 0.95 and 0.83 for the coronal plane, and 0.87 and 0.74 for the sagittal plane, respectively. Thus, the overall agreement was excellent, except for the sagittal imaging plane in group B.

Conclusion

This method using a commercially available workstation and liver analysis software can be useful for estimating the embolic area in cTACE.

Keywords

Cone beam computed tomography Hepatocellular carcinoma Transarterial chemoembolization 3-Dimensional workstation Real embolic area Virtual embolic area Virtual liver parenchymal perfusion area 

Notes

Acknowledgements

The authors would like to thank Yoshihiro Okayama (Clinical Trial Center for Development Therapeutics, Tokushima University Hospital) for his assistance with statistical analysis.

Compliance with Ethical Standards

Conflict of interest

The authors declared that they have no conflict of interest.

Ethical Approval

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

Informed Consent

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

References

  1. 1.
    Llovet JM, Bruix J. Systematic review of randomized trials for unresectable hepatocellular carcinoma: chemoembolization improves survival. Hepatology. 2003;37:429–42.CrossRefGoogle Scholar
  2. 2.
    Lo CM, Ngan H, Tso WK, Liu CL, Lam CM, Poon RT, Fan ST, Wong J. Randomized controlled trial of transcatheter lipiodol chemoembolization for unresectable hepatocellular carcinoma. Hepatology. 2002;35:1164–71.CrossRefGoogle Scholar
  3. 3.
    Miyayama S, Yamashiro M, Hashimoto M, Hashimoto N, Ikuno M, Okumura K, Yoshida M, Matsui O. Comparison of local control in transcatheter arterial chemoembolization of hepatocellular carcinoma ≤ 6 cm with or without intraprocedural monitoring of the embolized area using cone-beam computed tomography. Cardiovasc Intervent Radiol. 2014;37:388–95.CrossRefGoogle Scholar
  4. 4.
    Miyayama S, Yamashiro M, Hashimoto M, Hashimoto N, Ikuno M, Okumura K, Yoshida M, Matsui O. Identification of small hepatocellular carcinoma and tumor-feeding branches with cone-beam CT guidance technology during transcatheter arterial chemoembolization. J Vasc Interv Radiol. 2013;24:501–8.CrossRefGoogle Scholar
  5. 5.
    Miyayama S, Yamashiro M, Ikuno M, Okumura K, Yoshida M. Ultraselective transcatheter arterial chemoembolization for small hepatocellular carcinoma guided by automated tumor-feeders detection software: technical success and short-term tumor response. Abdom Imaging. 2014;39:645–56.CrossRefGoogle Scholar
  6. 6.
    Iwazawa J, Ohue S, Hashimoto N, Muramoto O, Mitani T. Clinical utility and limitations of tumor-feeder detection software for liver cancer embolization. Eur J Radiol. 2013;82:1665–71.CrossRefGoogle Scholar
  7. 7.
    Ronot M, Abdel-Rehim M, Hakimé A, Kuoch V, Roux M, Chiaradia M, Vilgrain V, de Baere T, Deschamps F. Cone-beam CT angiography for determination of tumor-feeding vessels during chemoembolization of liver tumors: comparison of conventional and dedicated-software analysis. J Vasc Interv Radiol. 2016;27:32–8.CrossRefGoogle Scholar
  8. 8.
    Miyayama S, Yamashiro M, Nagai K, Yokka A, Yoshida M, Sakuragawa N. Performance of novel virtual parenchymal perfusion software visualizing embolized areas of transcatheter arterial chemoembolization for hepatocellular carcinoma. Hepatol Res. 2017;47:446–54.CrossRefGoogle Scholar
  9. 9.
    Derbel H, Kobeiter H, Pizaine G, Ridouani F, Luciani A, Radaelli A, Van der Sterren W, Chiaradia M, Tacher V. Accuracy of a cone-beam CT virtual parenchymal perfusion algorithm for liver cancer targeting during intra-arterial therapy. J Vasc Interv Radiol. 2018;29:254–61.CrossRefGoogle Scholar
  10. 10.
    Ogawa C, Minami Y, Morita M, Noda T, Arasawa S, Izuta M, Kubo A, Matsunaka T, Tamaki H, Shibatoge M, Kudo M. Prediction of embolization area after conventional transcatheter arterial chemoembolization for hepatocellular carcinoma using SYNAPSE VINCENT. Dig Dis. 2016;34:696–701.CrossRefGoogle Scholar
  11. 11.
    Saito S, Yamanaka J, Miura K, Nakao N, Nagao T, Sugimoto T, Hirano T, Kuroda N, Iimuro Y, Fujimoto J. A novel 3D hepatectomy simulation based on liver circulation: application to liver resection and transplantation. Hepatology. 2005;41:1297–304.CrossRefGoogle Scholar
  12. 12.
    Takamoto T, Hashimoto T, Ogata S, Inoue K, Maruyama Y, Miyazaki A, Makuuchi M. Planning of anatomical liver segmentectomy and subsegmentectomy with 3-demensional simulation software. Am J Surg. 2013;206:530–8.CrossRefGoogle Scholar
  13. 13.
    Ohshima S. Volume analyzer SYNAPSE VINCENT for liver analysis. J Hepatobiliary Pancreat Sci. 2014;21:235–8.CrossRefGoogle Scholar
  14. 14.
    Oshiro Y, Yano H, Mitani J, Kim S, Kim J, Fukunaga K, Ohkohchi N. Novel 3-dimensional virtual hepatectomy simulation combined with real-time deformation. World J Gastroenterol. 2015;21:9982–92.CrossRefGoogle Scholar
  15. 15.
    Oppo K, Leen E, Angerson WJ, Cooke TG, McArdle CS. Doppler perfusion index: an interobserver and intraobserver reproducibility study. Radiology. 1998;208:453–7.CrossRefGoogle Scholar
  16. 16.
    Miyayama S, Matsui O, Yamashiro M, Ryu Y, Kitao K, Ozaki K, Takeda T, Yoneda N, Notsumata K, Toya D, Tanaka N, Mitsui T. Ultraselective transcatheter arterial chemoembolization with a 2-F tip microcatheter for small hepatocellular carcinoma: relationship between local tumor recurrence and visualization of the portal vein with iodized oil. J Vasc Interv Radiol. 2007;18:365–76.CrossRefGoogle Scholar
  17. 17.
    Miyayama S, Mitsui T, Zen Y, Sudo Y, Yamashiro M, Okuda M, Yoshie Y, Sanada T, Notsumata K, Tanaka N, Matsui O. Histopathological findings after ultraselective transcatheter arterial chemoembolization for hepatocellular carcinoma. Hepatol Res. 2009;39:374–81.CrossRefGoogle Scholar
  18. 18.
    Iwamoto S, Yamaguchi T, Hongo O, Iwamoto H, Sanefuji H. Excellent outcomes with angiographic subsegmentectomy in the treatment of typical hepatocellular carcinoma: a retrospective study of local recurrence and long-term survival rates in 120 patients with hepatocellular carcinoma. Cancer. 2010;116:393–9.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature and the Cardiovascular and Interventional Radiological Society of Europe (CIRSE) 2018

Authors and Affiliations

  • Mitsuhiro Kinoshita
    • 1
    Email author
  • Katsuya Takechi
    • 1
  • Yuta Arai
    • 2
  • Ryozo Shirono
    • 3
  • Yoshihiro Nagao
    • 4
  • Shoichi Izumi
    • 4
  • Takuya Akagawa
    • 4
  • Shiori Noda
    • 5
  • Shoichiro Takao
    • 6
  • Chikara Ogawa
    • 7
  • Daisuke Suwa
    • 8
  • Katsuyoshi Tamaki
    • 9
  • Naoto Uyama
    • 1
  • Yoko Akagawa
    • 1
  • Kyosuke Osaki
    • 1
  • Norio Ohnishi
    • 1
  • Hayato Tani
    • 1
  1. 1.Department of RadiologyTokushima Red Cross HospitalKomatsushima CityJapan
  2. 2.Department of Radiology (Diagnostic Radiology)Tokushima University HospitalTokushima CityJapan
  3. 3.Department of RadiologyKawashima-kai Kawashima HospitalTokushima CityJapan
  4. 4.Department of Radiological TechnologyTokushima Red Cross HospitalKomatsushima CityJapan
  5. 5.Graduate School of Health SciencesTokushima UniversityTokushima CityJapan
  6. 6.Department of Radiology and Radiation Oncology, Institute of Biomedical SciencesTokushima University Graduate SchoolTokushima CityJapan
  7. 7.Department of Gastroenterology and HepatologyTakamatsu Red Cross HospitalTakamatsu CityJapan
  8. 8.Department of Radiological TechnologyTakamatsu Red Cross HospitalTakamatsu CityJapan
  9. 9.Department of HepatologyTourai-kai Okubo HospitalTokushima CityJapan

Personalised recommendations