CardioVascular and Interventional Radiology

, Volume 40, Issue 5, pp 761–768

Development of a Searchable Database of Cryoablation Simulations for Use in Treatment Planning

  • F. Edward Boas
  • Govindarajan Srimathveeravalli
  • Jeremy C. Durack
  • Elena A. Kaye
  • Joseph P. Erinjeri
  • Etay Ziv
  • Majid Maybody
  • Hooman Yarmohammadi
  • Stephen B. Solomon
Technical Note
  • 116 Downloads

Abstract

Purpose

To create and validate a planning tool for multiple-probe cryoablation, using simulations of ice ball size and shape for various ablation probe configurations, ablation times, and types of tissue ablated.

Materials and Methods

Ice ball size and shape was simulated using the Pennes bioheat equation. Five thousand six hundred and seventy different cryoablation procedures were simulated, using 1–6 cryoablation probes and 1–2 cm spacing between probes. The resulting ice ball was measured along three perpendicular axes and recorded in a database. Simulated ice ball sizes were compared to gel experiments (26 measurements) and clinical cryoablation cases (42 measurements). The clinical cryoablation measurements were obtained from a HIPAA-compliant retrospective review of kidney and liver cryoablation procedures between January 2015 and February 2016. Finally, we created a web-based cryoablation planning tool, which uses the cryoablation simulation database to look up the probe spacing and ablation time that produces the desired ice ball shape and dimensions.

Results

Average absolute error between the simulated and experimentally measured ice balls was 1 mm in gel experiments and 4 mm in clinical cryoablation cases. The simulations accurately predicted the degree of synergy in multiple-probe ablations. The cryoablation simulation database covers a wide range of ice ball sizes and shapes up to 9.8 cm.

Conclusion

Cryoablation simulations accurately predict the ice ball size in multiple-probe ablations. The cryoablation database can be used to plan ablation procedures: given the desired ice ball size and shape, it will find the number and type of probes, probe configuration and spacing, and ablation time required.

Keywords

Cryoablation Simulation Prediction Planning 

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Copyright information

© Springer Science+Business Media New York and the Cardiovascular and Interventional Radiological Society of Europe (CIRSE) 2016

Authors and Affiliations

  • F. Edward Boas
    • 1
  • Govindarajan Srimathveeravalli
    • 1
  • Jeremy C. Durack
    • 1
  • Elena A. Kaye
    • 2
  • Joseph P. Erinjeri
    • 1
  • Etay Ziv
    • 1
  • Majid Maybody
    • 1
  • Hooman Yarmohammadi
    • 1
  • Stephen B. Solomon
    • 1
  1. 1.Department of RadiologyMemorial Sloan Kettering Cancer CenterNew YorkUSA
  2. 2.Department of Medical PhysicsMemorial Sloan Kettering Cancer CenterNew YorkUSA

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