3D Modelling of the Residual Freezing for Renal Cryoablation Simulation and Prediction

  • Caroline EssertEmail author
  • Pramod P. Rao
  • Afshin Gangi
  • Leo Joskowicz
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11768)


Percutaneous cryoablation has become a popular alternative to open surgery for the treatment of abdominal tumors. The preoperative planning of such interventions is an essential but complicated task. It consists in predicting the best placement for several cryoprobes to optimize the resulting iceball shape, that has to cover the whole tumor, while preserving healthy tissue and surrounding sensitive structures. In the past few years, methods have been proposed to simulate the propagation of cold within the tissue, in order to anticipate the final coverage. However, all the proposed models considered the source of cold as limited to the active tip of the cryoprobe, thus omitting a residual freezing along the probe’s body. The lack of precision of the resulting models can cause an underestimation of the predicted iceball leading to potential damages to healthy tissue or pain. In this paper, we describe the extension of an existing freezing simulation model to account for this effect. We detail the experimentation of our model on 5 retrospective cases, and demonstrate the improvement of the accuracy and realism of our simulation.



This work was partially supported by a grant from the Maimonide France-Israel Research in Biomedical Robotics, funded jointly by the French Ministry of Higher Education, Research and Innovation, the French Ministry for the Economy and Finance, and Israel Ministry of Science, Technology and Space, 2016–18, and by Grant 53681 (METASEG) from the Israel Ministry of Science, Technology and Space, 2016–2019.


  1. 1.
    Butz, T., et al.: Pre-and intra-operative planning and simulation of percutaneous tumor ablation. In: Delp, S.L., DiGoia, A.M., Jaramaz, B. (eds.) MICCAI 2000. LNCS, vol. 1935, pp. 317–326. Springer, Heidelberg (2000). Scholar
  2. 2.
    Ge, M., Chua, K., Shu, C., Yang, W.: Analytical and numerical study of tissue cryofreezing via the immersed boundary method. Int. J. Heat Mass Transfer 83, 1–10 (2015)CrossRefGoogle Scholar
  3. 3.
    Ge, M., Shu, C., Chua, K., Yang, W.: Numerical analysis of a clinically-extracted vascular tissue during cryo-freezing using immersed boundary method. Int. J. Therm. Sci. 110, 109–118 (2016)CrossRefGoogle Scholar
  4. 4.
    Ge, M., Shu, C., Yang, W., Chua, K.: Incorporating an immersed boundary method to study thermal effects of vascular systems during tissue cryo-freezing. J. Therm. Biol. 64, 92–99 (2017)CrossRefGoogle Scholar
  5. 5.
    Golkar, E., Rao, P.P., Joskowicz, L., Gangi, A., Essert, C.: Fast GPU computation of 3D isothermal volumes in the vicinity of major blood vessels for multiprobe cryoablation simulation. In: Frangi, A.F., Schnabel, J.A., Davatzikos, C., Alberola-López, C., Fichtinger, G. (eds.) MICCAI 2018. LNCS, vol. 11073, pp. 230–237. Springer, Cham (2018). Scholar
  6. 6.
    Hossain, S.C., Zhang, X., Haider, Z., Hu, P., Zhao, G.: Optimization of prostatic cryosurgery with multi-cryoprobe based on refrigerant flow. J. Therm. Biol. 76, 58–67 (2018)CrossRefGoogle Scholar
  7. 7.
    Kumar, A., Kumar, S., Katiyar, V., Telles, S.: Phase change heat transfer during cryosurgery of lung cancer using hyperbolic heat conduction model. Comput. Biol. Med. 84, 20–29 (2017)CrossRefGoogle Scholar
  8. 8.
    Kumar, M., Upadhyay, S., Rai, K.: A study of cryosurgery of lung cancer using modified legendre wavelet galerkin method. J. Therm. Biol. 78, 356–366 (2018)CrossRefGoogle Scholar
  9. 9.
    Magalov, Z., Shitzer, A., Degani, D.: Isothermal volume contours generated in a freezing gel by embedded cryo-needles with applications to cryo-surgery. Cryobiology 55(2), 127–137 (2007)CrossRefGoogle Scholar
  10. 10.
    Pennes, H.H.: Analysis of tissue and arterial blood temperatures in the resting human forearm. J. Appl. Physiol. 1(2), 93–122 (1948)CrossRefGoogle Scholar
  11. 11.
    Rieder, C., Kroeger, T., Schumann, C., Hahn, H.K.: GPU-based real-time approximation of the ablation zone for radiofrequency ablation. IEEE Trans. Visual. Comput. Graph. 17(12), 1812–1821 (2011)CrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Caroline Essert
    • 1
    Email author
  • Pramod P. Rao
    • 1
    • 2
  • Afshin Gangi
    • 1
    • 2
  • Leo Joskowicz
    • 3
  1. 1.ICube, Université de StrasbourgStrasbourgFrance
  2. 2.Department of RadiologyUniversity Hospital of StrasbourgStrasbourgFrance
  3. 3.CASMIP, The Hebrew University of JerusalemJerusalemIsrael

Personalised recommendations