Skip to main content
SpringerLink
Log in

Application of 3D imaging in the real-time US–CT fusion navigation for minimal invasive tumor therapy

  • Original Article
  • Published:
International Journal of Computer Assisted Radiology and Surgery Aims and scope Submit manuscript

Abstract

Purpose

Image-guided minimally invasive treatment (IG-MIT) has been widely used for local therapy of both benign and malignant tumors. However, precise needle targeting is a very important step in the minimally invasive treatment. Nowadays, minimally invasive treatment is usually performed with the guidance of the two-dimensional (2D) image. The tip of the puncture needle is difficult to place with precise positioning into the three-dimensional (3D) space of the tumor. This study was an experimental ex vivo study in porcine liver and heart samples with internal targets, focusing on the accuracy with the guidance of the real-time 3D imaging using a self-developed real-time ultrasonography and preoperative computed tomography (CT) fusion navigation system for minimal invasive tumor (liver tumor and uterine fibroid) therapy.

Methods

There are thirty porcine liver samples and thirty porcine heart samples used in the experiments. The average weight of the porcine liver samples was 2216.8 g, and the average weight of the porcine heart samples was 510.5 g. We conducted statistical analysis of the experimental results obtained by five medical students and five interventional radiologists.

Results

The puncture precision of the needle placement under the guidance of 3D imaging was significantly higher than that of the other groups, and the assistant function is more obvious for medical students than that for interventional radiologists \((p < 0.05)\). Assistant function of the US–CT fusion imaging is higher than that of the first group too \((p <0.05)\). The precision of the puncture with guidance of the 3D imaging was very satisfied in the fact that it was found that there was a mean discrepancy of \(2.7\pm 0.7\, \hbox {mm}\) (medical students) and \(1.8\pm 0.5\, \hbox {mm}\) (interventional radiologists) in porcine livers and there was a mean discrepancy of \(2.7\pm 0.8\, \hbox {mm}\) (medical students) and \(1.8\pm 0.5\, \hbox {mm}\) (interventional radiologists) in porcine hearts.

Conclusions

Experimental results showed that the accuracy of needle targeting can be improved with the guidance of the real-time 3D imaging than that with the guidance of both 2D US images and US–CT fusion images in IG-MIT. Assistant function of 3D imaging is obviously for medical students.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4

Similar content being viewed by others

References

  1. Livraghi T, Solbiati L, Meloni MF, Gazelle GS, Halpern EF, Goldberg SN (2003) Treatment of focal liver tumors with percutaneous radio-frequency ablation: complications encountered in a multicenter study. Radiology 226:441–451

    Article  PubMed  Google Scholar 

  2. Marquet F, Pernot M, Aubry JF, Tanter M, Montaldo G, Fink M (2006) In-vivo non-invasive motion tracking and correction in high intensity focused ultrasound therapy. Conf Proc IEEE Eng Med Biol Soc 1:688–691

    Article  PubMed  Google Scholar 

  3. Hinshaw JL, Lee FT Jr (2007) Cryoablation for liver cancer. Tech Vasc Interv Radiol 10:47–57

    Article  PubMed  Google Scholar 

  4. Liang P, Yu J, Yu XL, Wang XH, Wei Q, Yu SY, Li HX, Sun HT, Zhang ZX, Liu HC, Cheng ZG, Han ZY (2012) Percutaneous cooled-tip microwave ablation under ultrasound guidance for primary liver cancer: a multicentre analysis of 1363 treatment-naive lesions in 1007 patients in china. Gut 61:1100–1101

    Article  PubMed  Google Scholar 

  5. Xia M, Jing Z, Zhi-Yu H, Jian-Ming C, Hong-Yu Z, Rui-Fang X, Yu Y, Yan-Li H, Bao-Wei D (2014) Feasibility study on energy prediction of microwave ablation upon uterine adenomyosis and leiomyomas by mri. Br J Radiol 87:20130770

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  6. Yang Y, Zhang J, Han ZY, Yu MA, Ma X, Zhou HY, Hao YL, Zhao L, Dong XJ, Ge HL (2014) Ultrasound-guided percutaneous microwave ablation for submucosal uterine fibroids. J Minim Invasive Gynecol 21:436–441

    Article  PubMed  Google Scholar 

  7. Hildebrand P, Schlichting S, Martens V, Besirevic A, Kleemann M, Roblick U, Mirow L, Burk C, Schweikard A, Bruch HP (2008) Prototype of an intraoperative navigation and documentation system for laparoscopic radiofrequency ablation: first experiences. Eur J Surg Oncol 34:418–421

    Article  CAS  PubMed  Google Scholar 

  8. Yaniv Z, Cheng P, Wilson E, Popa T, Lindisch D, Campos-Nanez E, Abeledo H, Watson V, Cleary K, Banovac F (2010) Needle-based interventions with the image-guided surgery toolkit (igstk): from phantoms to clinical trials. IEEE Trans Biomed Eng 57:922–933

    Article  PubMed  Google Scholar 

  9. Liu FY, Yu XL, Liang P, Cheng ZG, Han ZY, Dong BW, Zhang XH (2012) Microwave ablation assisted by a real-time virtual navigation system for hepatocellular carcinoma undetectable by conventional ultrasonography. Eur J Radiol 81:1455–1459

    Article  PubMed  Google Scholar 

  10. Yu X, Liu F, Liang P, Era AD, Cheng Z, Han Z (2011) Microwave ablation assisted by a computerised tomography-ultrasonography fusion imaging system for liver lesions: an ex vivo experimental study. Int J Hyperth 27:172–179

    Article  Google Scholar 

  11. Clevert DA, Paprottka PM, Helck A, Reiser M, Trumm CG (2012) Image fusion in the management of thermal tumor ablation of the liver. Clin Hemorheol Microcirc 52:205–216

    CAS  PubMed  Google Scholar 

  12. Crocetti L, Lencioni R, Debeni S, See TC, Pina CD, Bartolozzi C (2008) Targeting liver lesions for radiofrequency ablation: an experimental feasibility study using a ct-us fusion imaging system. Invest Radiol 43:33–39

    Article  PubMed  Google Scholar 

  13. Marescaux J, Clement JM, Tassetti V, Koehl C, Cotin S, Russier Y, Mutter D, Delingette H, Ayache N (1998) Virtual reality applied to hepatic surgery simulation: the next revolution. Ann Surg 228:627–634

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  14. Harms J, Bartels M, Bourquain H, Peitgen HO, Schulz T, Kahn T, Hauss J, Fangmann J (2005) Computerized ct-based 3d visualization technique in living related liver transplantation. Transplant Proc 37:1059–1062

    Article  CAS  PubMed  Google Scholar 

  15. Hansen C, Kohn A, Schlichting S, Weiler F, Zidowitz S, Kleemann M, Peitgen HO (2008) Intraoperative modification of resection plans for liver surgery. Int J Comput Assist Radiol Surg 3:291–297

    Article  Google Scholar 

  16. Nanashima A, Abo T, Sakamoto I, Hayashi H, Fukuda T, Tobinaga S, Araki M, Sawai T, Nagayasu T (2012) Three-dimensional fusion images of hepatic vasculature and bile duct used for preoperative simulation before hepatic surgery. Hepatogastroenterology 59:1748–1757

    PubMed  Google Scholar 

  17. Spinczyk D (2014) Preparing the anatomical model for ablation of unresectable liver tumor. Wideochir Inne Tech Malo Inwazyjne 9:246–251

    PubMed Central  PubMed  Google Scholar 

  18. Wu W, Xue J, Liang P, Cheng Z, Zhang M, Mu M, Qi C (2014) The assistant function of three-dimensional information for i125 particle implantation. IEEE J Biomed Health Inform 18:77–82

    Article  PubMed  Google Scholar 

  19. Lu T, Liang P, Wu WB, Xue J, Lei CL, Li YY, Sun YN, Liu FY (2012) Integration of the image-guided surgery toolkit (igstk) into the medical imaging interaction toolkit (mitk). J Digit Imaging 25:729–737

    Article  PubMed Central  PubMed  Google Scholar 

  20. Liu F, Liang P, Yu X, Lu T, Cheng Z, Lei C, Han Z (2013) A three-dimensional visualisation preoperative treatment planning system in microwave ablation for liver cancer: A preliminary clinical application. Int J Hyperth 29:671–677

    Article  Google Scholar 

  21. Wu W, Xue Y, Wang D, Xue J, Zhai W, Liang P (2014) A simulator for percutaneous hepatic microwave thermal ablation under ultrasound guidance. Int J Hyperth 30:429–437

    Article  Google Scholar 

  22. Huang W, Tan ZM, Lin Z, Huang GB, Zhou J, Chui CK, Su Y, Chang S (2012) A semi-automatic approach to the segmentation of liver parenchyma from 3d ct images with extreme learning machine. Conf Proc IEEE Eng Med Biol Soc 2012:3752–3755

    CAS  PubMed  Google Scholar 

  23. Muller MA, Marincek B, Frauenfelder T (2007) State of the art 3d imaging of abdominal organs. JBR-BTR 90:467–474

    CAS  PubMed  Google Scholar 

  24. Enokizono M, Morikawa M, Matsuo T, Hayashi T, Horie N, Honda S, Ideguchi R, Nagata I, Uetani M (2014) The rim pattern of meningioma on 3d flair imaging: correlation with tumor-brain adhesion and histological grading. Magn Reson Med Sci 13(4):251–260

    Article  PubMed  Google Scholar 

  25. Appelbaum L, Mahgerefteh SY, Sosna J, Goldberg SN (2013) Image-guided fusion and navigation: applications in tumor ablation. Tech Vasc Interv Radiol 16:287–295

    Article  PubMed  Google Scholar 

Download references

Acknowledgments

This work was supported by the National Key Technology R&D Program of China (2013BAI01B01), and by the National Natural Science Foundation of China (81430039).

Conflict of interest

The authors have no conflict of interest.

Author information

Author notes

    Authors and Affiliations

    1. Department of Interventional Ultrasound, Chinese PLA General Hospital, Beijing, China

      Wenbo Wu, Jin Xue & Shaobo Duan

    2. Department of Gynaecology, Zoucheng People’s Hospital, 59 Qianquan Road, Zoucheng, Shandong, 273500, China

      Yingfeng Xue & Jin Xue

    3. Department of Orthopedic, Zoucheng People’s Hospital, Shandong, China

      Dong Wang

    4. Department of Radiology, Zoucheng People’s Hospital, Shandong, China

      Xiaoguang Li

    5. Department of Neurology, Zoucheng People’s Hospital, Shandong, China

      Fang Wang

    Authors
    1. Wenbo Wu
      View author publications

      You can also search for this author in PubMed Google Scholar

    2. Yingfeng Xue
      View author publications

      You can also search for this author in PubMed Google Scholar

    3. Dong Wang
      View author publications

      You can also search for this author in PubMed Google Scholar

    4. Xiaoguang Li
      View author publications

      You can also search for this author in PubMed Google Scholar

    5. Jin Xue
      View author publications

      You can also search for this author in PubMed Google Scholar

    6. Shaobo Duan
      View author publications

      You can also search for this author in PubMed Google Scholar

    7. Fang Wang
      View author publications

      You can also search for this author in PubMed Google Scholar

    Corresponding author

    Correspondence to Jin Xue.

    Additional information

    Wenbo Wu and Yingfeng Xue have contributed equally to this work as co-first authors.

    Rights and permissions

    Reprints and permissions

    About this article

    Check for updates. Verify currency and authenticity via CrossMark

    Cite this article

    Wu, W., Xue, Y., Wang, D. et al. Application of 3D imaging in the real-time US–CT fusion navigation for minimal invasive tumor therapy. Int J CARS 10, 1651–1658 (2015). https://doi.org/10.1007/s11548-015-1224-z

    Download citation

    • Received:

    • Accepted:

    • Published:

    • Issue Date:

    • DOI: https://doi.org/10.1007/s11548-015-1224-z

    Keywords

    Search

    Navigation