Dataset Information

Time-Dependent Finite Element Analysis of In Vivo Electrochemotherapy Treatment.

ABSTRACT: Electrochemotherapy and irreversible electroporation are gaining importance in clinical practice for the treatment of solid tumors. For successful treatment, it is extremely important that the coverage and exposure time of the treated tumor to the electric field are within the specified range. In order to ensure successful coverage of the entire target volume with sufficiently strong electric fields, numerical treatment planning has been proposed and its use has also been demonstrated in practice. Most of numerical models in treatment planning are based on charge conservation equation and are not able to provide time course of electric current, electrical conductivity, or electric field distribution changes established in the tissue during pulse delivery. Recently, a model based on inverse analysis of experimental data that delivers time course of tissue electroporation has been introduced. The aim of this study was to apply the previously reported time-dependent numerical model to a complex in vivo example of electroporation with different tissue types and with a long-term follow-up. The model, consisting of a tumor placed in the liver with 2 needle electrodes inserted in the center of the tumor and 4 around the tumor, was validated by comparison of measured and calculated time course of applied electric current. Results of simulations clearly indicated that proposed numerical model can successfully capture transient effects, such as evolution of electric current during each pulse, and effects of pulse frequency due to electroporation effects in the tissue. Additionally, the model can provide evolution of electric field amplitude and electrical conductivity in the tumor with consecutive pulse sequences.

SUBMITTER: Pintar M

PROVIDER: S-EPMC6083743 | biostudies-literature | 2018 Jan

REPOSITORIES: biostudies-literature

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Time-Dependent Finite Element Analysis of In Vivo Electrochemotherapy Treatment.

Pintar Matevž M Langus Janez J Edhemović Ibrahim I Brecelj Erik E Kranjc Matej M Sersa Gregor G Šuštar Tomaž T Rodič Tomaž T Miklavčič Damijan D Kotnik Tadej T Kos Bor B

Technology in cancer research & treatment 20180101

Electrochemotherapy and irreversible electroporation are gaining importance in clinical practice for the treatment of solid tumors. For successful treatment, it is extremely important that the coverage and exposure time of the treated tumor to the electric field are within the specified range. In order to ensure successful coverage of the entire target volume with sufficiently strong electric fields, numerical treatment planning has been proposed and its use has also been demonstrated in practic ...[more]

PMID: 30089424

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Project description:BACKGROUND: Biological mass transport processes determine the behavior and function of cells, regulate interactions between synthetic agents and recipient targets, and are key elements in the design and use of biosensors. Accurately predicting the outcomes of such processes is crucial to both enhancing our understanding of how these systems function, enabling the design of effective strategies to control their function, and verifying that engineered solutions perform according to plan. METHODS: A Galerkin-based finite element model was developed and implemented to solve a system of two coupled partial differential equations governing biomolecule transport and reaction in live cells. The simulator was coupled, in the framework of an inverse modeling strategy, with an optimization algorithm and an experimental time series, obtained by the Fluorescence Recovery after Photobleaching (FRAP) technique, to estimate biomolecule mass transport and reaction rate parameters. In the inverse algorithm, an adaptive method was implemented to calculate sensitivity matrix. A multi-criteria termination rule was developed to stop the inverse code at the solution. The applicability of the model was illustrated by simulating the mobility and binding of GFP-tagged glucocorticoid receptor in the nucleoplasm of mouse adenocarcinoma. RESULTS: The numerical simulator shows excellent agreement with the analytic solutions and experimental FRAP data. Detailed residual analysis indicates that residuals have zero mean and constant variance and are normally distributed and uncorrelated. Therefore, the necessary and sufficient criteria for least square parameter optimization, which was used in this study, were met. CONCLUSION: The developed strategy is an efficient approach to extract as much physiochemical information from the FRAP protocol as possible. Well-posedness analysis of the inverse problem, however, indicates that the FRAP protocol provides insufficient information for unique simultaneous estimation of diffusion coefficient and binding rate parameters. Care should be exercised in drawing inferences, from FRAP data, regarding concentrations of free and bound proteins, average binding and diffusion times, and protein mobility unless they are confirmed by long-range Markov Chain-Monte Carlo (MCMC) methods and experimental observations.

Project description:Radiofrequency ablation is the most common minimally invasive therapy used in the United States to treat hepatocellular carcinoma and liver metastases. The ability to perform real-time temperature imaging while a patient is undergoing ablation therapy may help reduce the high recurrence rates following ablation therapy. Ultrasound echo signals undergo time shifts with increasing temperature due to sound speed and thermal expansion, which are tracked using both 1D cross correlation and 2D block matching based speckle tracking methods. In this paper, we present a quantitative evaluation of the accuracy and precision of temperature estimation using the above algorithms on both simulated and experimental data. A finite element analysis simulation of radiofrequency ablation of hepatic tissue was developed. Finite element analysis provides a method to obtain the exact temperature distribution along with a mapping of the tissue displacement due to thermal expansion. These local displacement maps were combined with the displacement due to speed of sound changes and utilized to generate ultrasound radiofrequency frames at specified time increments over the entire ablation procedure. These echo signals provide an ideal test-bed to evaluate the performance of both speckle tracking methods, since the estimated temperature results can be compared directly to the exact finite element solution. Our results indicate that the 1D cross-correlation (CC) method underestimates the cumulative displacement by 0.20mm, while the underestimation with 2D block matching (BM) is about 0.14 mm after 360 s of ablation. The 1D method also overestimates the size of the ablated region by 5.4% when compared to 2.4% with the 2D method after 720 s of ablation. Hence 2D block matching provides better tracking of temperature variations when compared to the 1D cross-correlation method over the entire duration of the ablation procedure. In addition, results obtained using 1D cross-correlation diverge from the ideal finite element results after 7 min of ablation and for temperatures greater than 65 degrees C. In a similar manner, experimental results presented using a tissue-mimicking phantom also demonstrate that the maximum percent difference with 2D block matching was 5%, when compared to 31% with the 1D method over the 700 s heating duration on the phantom.

Dataset Information

Time-Dependent Finite Element Analysis of In Vivo Electrochemotherapy Treatment.

Publications

Time-Dependent Finite Element Analysis of In Vivo Electrochemotherapy Treatment.

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