<abstract xml:lang="en" xmlns="http://www.w3.org/1999/xhtml"><bold><italic>Background.</italic></bold> In addition to the chemotherapeutic drug being present within the tumor during electric pulse delivery, successful electrochemotherapy requires the entire tumor volume to be subjected to a sufficiently high electric field, while the electric field in the surrounding healthy tissue is as low as possible to prevent damage. Both can be achieved with appropriate positioning of the electrodes and appropriate amplitude of electric pulses.<bold><italic>Methods.</italic></bold> We used 3D finite element numerical models and a genetic optimization algorithm to determine the optimum electrode configuration and optimum amplitude of electric pulses for treatment of three subcutaneous tumor models of different shapes and sizes and a realistic brain tumor model acquired from medical images.<bold><italic>Results.</italic></bold> In all four tumor cases, parallel needle electrode arrays were a better choice than hexagonal needle electrode arrays, since their utilization required less electric current and caused less healthy tissue damage. In addition, regardless of tumor geometry or needle electrode configuration, the optimum depth of electrode insertion was in all cases deeper than the deepest part of the tumor.<bold><italic>Conclusions.</italic></bold> Our optimization algorithm was able to determine the best electrode configuration in all four presented models and with further improvement it could be a useful tool in clinical electrochemotherapy treatment planning.</abstract>

Background. In addition to the chemotherapeutic drug being present within the tumor during electric pulse delivery, successful electrochemotherapy requires the entire tumor volume to be subjected to a sufficiently high electric field, while the electric field in the surrounding healthy tissue is as low as possible to prevent damage. Both can be achieved with appropriate positioning of the electrodes and appropriate amplitude of electric pulses.Methods. We used 3D finite element numerical models and a genetic optimization algorithm to determine the optimum electrode configuration and optimum amplitude of electric pulses for treatment of three subcutaneous tumor models of different shapes and sizes and a realistic brain tumor model acquired from medical images.Results. In all four tumor cases, parallel needle electrode arrays were a better choice than hexagonal needle electrode arrays, since their utilization required less electric current and caused less healthy tissue damage. In addition, regardless of tumor geometry or needle electrode configuration, the optimum depth of electrode insertion was in all cases deeper than the deepest part of the tumor.Conclusions. Our optimization algorithm was able to determine the best electrode configuration in all four presented models and with further improvement it could be a useful tool in clinical electrochemotherapy treatment planning.

Optimization of electrode position and electric pulse amplitude in electrochemotherapy

Faculty of Electrical Engineering, University of Ljubljana, Ljubljana, Slovenia

Radiology and Oncology

Background. In addition to the chemotherapeutic drug being present within the tumor during electric pulse delivery, successful electrochemotherapy requires the...

Optimization of electrode position and electric pulse amplitude in electrochemotherapy

Published Online: Jun 11, 2008

Page range: 93 - 101

DOI: https://doi.org/10.2478/v10019-008-0005-5

Keywords
electrochemotherapy, electroporation, subcutaneous tumor, finite element method, numerical modeling, optimization

This content is open access.

Optimization of electrode position and electric pulse amplitude in electrochemotherapy

Published Online: Jun 11, 2008

Page range: 93 - 101

DOI: https://doi.org/10.2478/v10019-008-0005-5

Keywordselectrochemotherapy, electroporation, subcutaneous tumor, finite element method, numerical modeling, optimization

This content is open access.

Keywords
electrochemotherapy, electroporation, subcutaneous tumor, finite element method, numerical modeling, optimization