Electrical Characterization of Human Biological Tissue for Irreversible Electroporation Treatments

Irreversible electroporation (IRE) is a cancer therapy that uses short, high-voltage electrical pulses to treat tumors. Due to its predominantly non-thermal mechanism and ability to ablate unresectable tumors, IRE has gained popularity in clinical treatments of both liver and pancreatic cancers. Exi...

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Bibliographic Details
Published in2018 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) Vol. 2018; pp. 4170 - 4173
Main Authors Beitel-White, Natalie, Bhonsle, Suyashree, Martin, R. C. G., Davalos, Rafael V.
Format Conference Proceeding Journal Article
LanguageEnglish
Published United States IEEE 01.07.2018
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Summary:Irreversible electroporation (IRE) is a cancer therapy that uses short, high-voltage electrical pulses to treat tumors. Due to its predominantly non-thermal mechanism and ability to ablate unresectable tumors, IRE has gained popularity in clinical treatments of both liver and pancreatic cancers. Existing computational models use electrical properties of animal tissue that are quantified a priori to predict the area of treatment in three dimensions. However, the changes in the electrical properties of human tissue during IRE treatment are so far unexplored. This work aims to improve models by characterizing the dynamic electrical behavior of human liver and pancreatic tissue. Fresh patient samples of each tissue type, both normal and tumor, were collected and IRE pulses were applied between two parallel metal plates at various voltages. The electrical conductivity was determined from the resistance using simple relations applicable to cylindrical samples. The results indicate that the percent change in conductivity during IRE treatments varies significantly with increasing electric field magnitudes. This percent change versus applied electric field behavior can be fit to a sigmoidal curve, as proposed in prior studies. The generic conductivity data from human patients from this work can be input to computational software using patient-specific geometry, giving clinicians a more accurate and personalized prediction of a given IRE treatment.
ISSN:1557-170X
1558-4615
DOI:10.1109/EMBC.2018.8513341