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    ABSTRACT: Magnetic resonance electrical impedance tomography (MREIT) was recently proposed for determining electric field distribution during electroporation in which cell membrane permeability is temporary increased by application of an external high electric field. The method was already successfully applied for reconstruction of electric field distribution in agar phantoms. Before the next step towards in vivo experiments is taken, monitoring of electric field distribution during electroporation of ex vivo tissue ex vivo and feasibility for its use in electroporation based treatments needed to be evaluated. Sequences of high voltage pulses were applied to chicken liver tissue in order to expose it to electric field which was measured by means of MREIT. MREIT was also evaluated for its use in electroporation based treatments by calculating electric field distribution for two regions, the tumor and the tumor-liver region, in a numerical model based on data obtained from clinical study on electrochemotherapy treatment of deep-seated tumors. Electric field distribution inside tissue was successfully measured ex vivo using MREIT and significant changes of tissue electrical conductivity were observed in the region of the highest electric field. A good agreement was obtained between the electric field distribution obtained by MREIT and the actual electric field distribution in evaluated regions of a numerical model, suggesting that implementation of MREIT could thus enable efficient detection of areas with insufficient electric field coverage during electroporation based treatments, thus assuring the effectiveness of the treatment.
    PLoS ONE 01/2012; 7(9):e45737. · 3.53 Impact Factor
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    ABSTRACT: Here, theoretical relationships between the parameters of the electric pulse, which is necessary to porate the cell by electric pulse of various shapes, have been obtained. The theoretical curves were compared with the experimental relationships. Experiments were carried out with human erythrocytes and mouse hepatoma MH-22A cells. The fraction of electroporated MH-22A cells was determined from the extent of the release of intracellular potassium ions and erythrocytes – from the extent of their hemolysis after long (20–24 h) incubation in 0.63% NaCl solution at 4 oC. The dependence of the fraction of electroporated cells on the amplitude of the electric field pulse was determined for pulses with the duration from 95 ns to 2 ms. The shapes of theoretical dependencies are in agreement with experimental ones. The cell poration time depended on the intensity of the pulse: the shorter the pulse duration, the higher the electric field strength has to be. This dependence is much more pronounced for pulses shorter than 1 μs. For example, if the pulse amplitude required to electroporate 50% of human erythrocytes increased from 1.0 to 1.76 kV/cm, when the duration of a square-wave pulse was reduced from 2 ms to 20 μs, it increased from 3 to 12 kV/cm, when the pulse duration was reduced from 950 to 95 ns. The relationships between the electric field strength required for electroporation and the frequency of the applied ac field were calculated for different pulse lengths. It has been obtained that although the electric field strength is constant for frequencies less than 10 kHz but its value depends on the pulse length decreasing with increasing pulse duration. At higher frequencies electric field strength is dependent on the frequency of the ac field.
    IEEE Transactions on Plasma Science 10/2013; 41(10):2913-2919. · 0.87 Impact Factor
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    ABSTRACT: BACKGROUND: Electroporation based therapies and treatments (e.g. electrochemotherapy, gene electrotransfer for gene therapy and DNA vaccination, tissue ablation with irreversible electroporation and transdermal drug delivery) require a precise prediction of the therapy or treatment outcome by a personalized treatment planning procedure. Numerical modeling of local electric field distribution within electroporated tissues has become an important tool in treatment planning procedure in both clinical and experimental settings. Recent studies have reported that the uncertainties in electrical properties (i.e. electric conductivity of the treated tissues and the rate of increase in electric conductivity due to electroporation) predefined in numerical models have large effect on electroporation based therapy and treatment effectiveness. The aim of our study was to investigate whether the increase in electric conductivity of tissues needs to be taken into account when modeling tissue response to the electroporation pulses and how it affects the local electric distribution within electroporated tissues. METHODS: We built 3D numerical models for single tissue (one type of tissue, e.g. liver) and composite tissue (several types of tissues, e.g. subcutaneous tumor). Our computer simulations were performed by using three different modeling approaches that are based on finite element method: inverse analysis, nonlinear parametric and sequential analysis. We compared linear (i.e. tissue conductivity is constant) model and non-linear (i.e. tissue conductivity is electric field dependent) model. By calculating goodness of fit measure we compared the results of our numerical simulations to the results of in vivo measurements. RESULTS: The results of our study show that the nonlinear models (i.e. tissue conductivity is electric field dependent: sigma(E)) fit experimental data better than linear models (i.e. tissue conductivity is constant). This was found for both single tissue and composite tissue. Our results of electric field distribution modeling in linear model of composite tissue (i.e. in the subcutaneous tumor model that do not take into account the relationship sigma(E)) showed that a very high electric field (above irreversible threshold value) was concentrated only in the stratum corneum while the target tumor tissue was not successfully treated. Furthermore, the calculated volume of the target tumor tissue exposed to the electric field above reversible threshold in the subcutaneous model was zero assuming constant conductivities of each tissue.Our results also show that the inverse analysis allows for identification of both baseline tissue conductivity (i.e. conductivity of non-electroporated tissue) and tissue conductivity vs. electric field (sigma(E)) of electroporated tissue. CONCLUSION: Our results of modeling of electric field distribution in tissues during electroporation show that the changes in electrical conductivity due to electroporation need to be taken into account when an electroporation based treatment is planned or investigated. We concluded that the model of electric field distribution that takes into account the increase in electric conductivity due to electroporation yields more precise prediction of successfully electroporated target tissue volume. The findings of our study can significantly contribute to the current development of individualized patient-specific electroporation based treatment planning.
    BioMedical Engineering OnLine 02/2013; 12(1):16. · 1.61 Impact Factor

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