A parametric study delineating irreversible electroporation from thermal damage based on a minimally invasive intracranial procedure

Biomed Eng Online. 2011 Apr 30:10:34. doi: 10.1186/1475-925X-10-34.

Abstract

Background: Irreversible electroporation (IRE) is a new minimally invasive technique to kill undesirable tissue in a non-thermal manner. In order to maximize the benefits from an IRE procedure, the pulse parameters and electrode configuration must be optimized to achieve complete coverage of the targeted tissue while preventing thermal damage due to excessive Joule heating.

Methods: We developed numerical simulations of typical protocols based on a previously published computed tomographic (CT) guided in vivo procedure. These models were adapted to assess the effects of temperature, electroporation, pulse duration, and repetition rate on the volumes of tissue undergoing IRE alone or in superposition with thermal damage.

Results: Nine different combinations of voltage and pulse frequency were investigated, five of which resulted in IRE alone while four produced IRE in superposition with thermal damage.

Conclusions: The parametric study evaluated the influence of pulse frequency and applied voltage on treatment volumes, and refined a proposed method to delineate IRE from thermal damage. We confirm that determining an IRE treatment protocol requires incorporating all the physical effects of electroporation, and that these effects may have significant implications in treatment planning and outcome assessment. The goal of the manuscript is to provide the reader with the numerical methods to assess multiple-pulse electroporation treatment protocols in order to isolate IRE from thermal damage and capitalize on the benefits of a non-thermal mode of tissue ablation.

Publication types

  • Research Support, Non-U.S. Gov't
  • Research Support, U.S. Gov't, Non-P.H.S.

MeSH terms

  • Animals
  • Brain / cytology*
  • Dogs
  • Electric Conductivity
  • Electroporation*
  • Hot Temperature / adverse effects*
  • Models, Biological*
  • Time Factors