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A statistical model describing combined irreversible electroporation and electroporation-induced blood-brain barrier disruption

BACKGROUND: Electroporation-based therapies such as electrochemotherapy (ECT) and irreversible electroporation (IRE) are emerging as promising tools for treatment of tumors. When applied to the brain, electroporation can also induce transient blood-brain-barrier (BBB) disruption in volumes extending...

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Autores principales: Sharabi, Shirley, Kos, Bor, Last, David, Guez, David, Daniels, Dianne, Harnof, Sagi, Mardor, Yael, Miklavcic, Damijan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: De Gruyter 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4825337/
https://www.ncbi.nlm.nih.gov/pubmed/27069447
http://dx.doi.org/10.1515/raon-2016-0009
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author Sharabi, Shirley
Kos, Bor
Last, David
Guez, David
Daniels, Dianne
Harnof, Sagi
Mardor, Yael
Miklavcic, Damijan
author_facet Sharabi, Shirley
Kos, Bor
Last, David
Guez, David
Daniels, Dianne
Harnof, Sagi
Mardor, Yael
Miklavcic, Damijan
author_sort Sharabi, Shirley
collection PubMed
description BACKGROUND: Electroporation-based therapies such as electrochemotherapy (ECT) and irreversible electroporation (IRE) are emerging as promising tools for treatment of tumors. When applied to the brain, electroporation can also induce transient blood-brain-barrier (BBB) disruption in volumes extending beyond IRE, thus enabling efficient drug penetration. The main objective of this study was to develop a statistical model predicting cell death and BBB disruption induced by electroporation. This model can be used for individual treatment planning. MATERIAL AND METHODS: Cell death and BBB disruption models were developed based on the Peleg-Fermi model in combination with numerical models of the electric field. The model calculates the electric field thresholds for cell kill and BBB disruption and describes the dependence on the number of treatment pulses. The model was validated using in vivo experimental data consisting of rats brains MRIs post electroporation treatments. RESULTS: Linear regression analysis confirmed that the model described the IRE and BBB disruption volumes as a function of treatment pulses number (r(2) = 0.79; p < 0.008, r(2) = 0.91; p < 0.001). The results presented a strong plateau effect as the pulse number increased. The ratio between complete cell death and no cell death thresholds was relatively narrow (between 0.88-0.91) even for small numbers of pulses and depended weakly on the number of pulses. For BBB disruption, the ratio increased with the number of pulses. BBB disruption radii were on average 67% ± 11% larger than IRE volumes. CONCLUSIONS: The statistical model can be used to describe the dependence of treatment-effects on the number of pulses independent of the experimental setup.
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spelling pubmed-48253372016-04-11 A statistical model describing combined irreversible electroporation and electroporation-induced blood-brain barrier disruption Sharabi, Shirley Kos, Bor Last, David Guez, David Daniels, Dianne Harnof, Sagi Mardor, Yael Miklavcic, Damijan Radiol Oncol Research Article BACKGROUND: Electroporation-based therapies such as electrochemotherapy (ECT) and irreversible electroporation (IRE) are emerging as promising tools for treatment of tumors. When applied to the brain, electroporation can also induce transient blood-brain-barrier (BBB) disruption in volumes extending beyond IRE, thus enabling efficient drug penetration. The main objective of this study was to develop a statistical model predicting cell death and BBB disruption induced by electroporation. This model can be used for individual treatment planning. MATERIAL AND METHODS: Cell death and BBB disruption models were developed based on the Peleg-Fermi model in combination with numerical models of the electric field. The model calculates the electric field thresholds for cell kill and BBB disruption and describes the dependence on the number of treatment pulses. The model was validated using in vivo experimental data consisting of rats brains MRIs post electroporation treatments. RESULTS: Linear regression analysis confirmed that the model described the IRE and BBB disruption volumes as a function of treatment pulses number (r(2) = 0.79; p < 0.008, r(2) = 0.91; p < 0.001). The results presented a strong plateau effect as the pulse number increased. The ratio between complete cell death and no cell death thresholds was relatively narrow (between 0.88-0.91) even for small numbers of pulses and depended weakly on the number of pulses. For BBB disruption, the ratio increased with the number of pulses. BBB disruption radii were on average 67% ± 11% larger than IRE volumes. CONCLUSIONS: The statistical model can be used to describe the dependence of treatment-effects on the number of pulses independent of the experimental setup. De Gruyter 2016-02-16 /pmc/articles/PMC4825337/ /pubmed/27069447 http://dx.doi.org/10.1515/raon-2016-0009 Text en © 2016 Radiol Oncol
spellingShingle Research Article
Sharabi, Shirley
Kos, Bor
Last, David
Guez, David
Daniels, Dianne
Harnof, Sagi
Mardor, Yael
Miklavcic, Damijan
A statistical model describing combined irreversible electroporation and electroporation-induced blood-brain barrier disruption
title A statistical model describing combined irreversible electroporation and electroporation-induced blood-brain barrier disruption
title_full A statistical model describing combined irreversible electroporation and electroporation-induced blood-brain barrier disruption
title_fullStr A statistical model describing combined irreversible electroporation and electroporation-induced blood-brain barrier disruption
title_full_unstemmed A statistical model describing combined irreversible electroporation and electroporation-induced blood-brain barrier disruption
title_short A statistical model describing combined irreversible electroporation and electroporation-induced blood-brain barrier disruption
title_sort statistical model describing combined irreversible electroporation and electroporation-induced blood-brain barrier disruption
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4825337/
https://www.ncbi.nlm.nih.gov/pubmed/27069447
http://dx.doi.org/10.1515/raon-2016-0009
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