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Parametric optimization of electric field strength for cancer electrochemotherapy on a chip-based model.

ABSTRACT: Electrochemotherapy (ECT), as one of the very few available treatments for cutaneous and subcutaneous tumors when surgery and radiotherapy are no longer available, requires applying a proper electric field to the tumor to realize electroporation-mediated cytotoxic drug delivery. It is impossible to exhaust all possible electrical parameters on patients to realize the optimal tradeoff between tumor suppression and adverse effects. To address this issue, this study provides a feasible solution by developing a four-leaf micro-electrode chip (F-MEC) in which the electric field was specially designed by linear distribution to cover all possible electric field strengths for ECT. Methods: We developed a F-MEC that provides a linearly varied electric field and a capacity for in situ observation of cell status. By culturing tumor cells on the F-MEC surface and in situ monitoring the cell responses to ECT drugs, the optimal electric field strength for any given cell type could be rapidly and accurately calculated in a few, or even only one, simple assay. Results: Using this chip, we monitored MCF-7 and A315 cell responses to ECT and determined the optimum ECT voltage. More importantly, we successfully verified that the in vitro determined voltage coincided with the optimal value for in vivo ECT in mice. Conclusion: In this proof-of-concept study, the in vivo tumor suppression assays proved that the optimal parameters acquired from in vitro F-MEC assay could be used for in vivo ECT.

SUBMITTER: Zhao D

PROVIDER: S-EPMC5743553 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature

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Parametric optimization of electric field strength for cancer electrochemotherapy on a chip-based model.

Zhao Deyao D Wu Mengxi M Huang Dong D Liang Zicai Z Wei Zewen Z Li Zhihong Z

Theranostics 20180101 2

Electrochemotherapy (ECT), as one of the very few available treatments for cutaneous and subcutaneous tumors when surgery and radiotherapy are no longer available, requires applying a proper electric field to the tumor to realize electroporation-mediated cytotoxic drug delivery. It is impossible to exhaust all possible electrical parameters on patients to realize the optimal tradeoff between tumor suppression and adverse effects. To address this issue, this study provides a feasible solution by ...[more]

PMID: 29290813

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Project description:BackgroundDuring transcranial magnetic stimulation (TMS) a coil placed on the scalp is used to non-invasively modulate activity of targeted brain networks via a magnetically induced electric field (E-field). Ideally, the E-field induced during TMS is concentrated on a targeted cortical region of interest (ROI). Determination of the coil position and orientation that best achieve this objective presently requires a large computational effort.ObjectiveTo improve the accuracy of TMS we have developed a fast computational auxiliary dipole method (ADM) for determining the optimum coil position and orientation. The optimum coil placement maximizes the E-field along a predetermined direction or, alternatively, the overall E-field magnitude in the targeted ROI. Furthermore, ADM can assess E-field uncertainty resulting from precision limitations of TMS coil placement protocols.MethodADM leverages the electromagnetic reciprocity principle to compute rapidly the TMS induced E-field in the ROI by using the E-field generated by a virtual constant current source residing in the ROI. The framework starts by solving for the conduction currents resulting from this ROI current source. Then, it rapidly determines the average E-field induced in the ROI for each coil position by using the conduction currents and a fast-multipole method. To further speed-up the computations, the coil is approximated using auxiliary dipoles enabling it to represent all coil orientations for a given coil position with less than 600 dipoles.ResultsUsing ADM, the E-fields generated in an MRI-derived head model when the coil is placed at 5900 different scalp positions and 360 coil orientations per position (over 2.1 million unique configurations) can be determined in under 15 min on a standard laptop computer. This enables rapid extraction of the optimum coil position and orientation as well as the E-field variation resulting from coil positioning uncertainty. ADM is implemented in SimNIBS 3.2.ConclusionADM enables the rapid determination of coil placement that maximizes E-field delivery to a specific brain target. This method can find the optimum coil placement in under 15 min enabling its routine use for TMS. Furthermore, it enables the fast quantification of uncertainty in the induced E-field due to limited precision of TMS coil placement protocols, enabling minimization and statistical analysis of the E-field dose variability.

Dataset Information

Parametric optimization of electric field strength for cancer electrochemotherapy on a chip-based model.

Publications

Parametric optimization of electric field strength for cancer electrochemotherapy on a chip-based model.

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