TY - JOUR
T1 - Heat conduction in live tissue during radiofrequency electrosurgery
AU - Ran, Junren
AU - El-Kebir, Hamza
AU - Lee, Yongseok
AU - Chamorro, Leonardo P.
AU - Berlin, Richard
AU - Cornejo, Gabriela M.Aguiluz
AU - Benedetti, Enrico
AU - Giulianotti, Pier C.
AU - Bhargava, Rohit
AU - Bentsman, Joseph
AU - Ostoja-Starzewski, Martin
N1 - Experimental data reported in this publication were supported by the National Institute of Biomedical Imaging and Bioengineering of the National Institutes of Health under award no. R01EB029766, as part of the NSF/DHS/DOT/NIH/USDANIFA Cyber-Physical Systems Program. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.
PY - 2024/1/17
Y1 - 2024/1/17
N2 - In this paper, we propose a method to model radiofrequency electrosurgery to capture the phenomena at higher temperatures and present the methods for parameter estimation. Experimental data taken from our surgical trials performed on in vivo porcine liver show that a non-Fourier Maxwell- Cattaneo-type model can be suitable for this application when used in combination with an Arrhenius-type model that approximates the energy dissipation in physical and chemical reactions. The resulting model structure has the advantage of higher accuracy than existing ones, while reducing the computation time required.
AB - In this paper, we propose a method to model radiofrequency electrosurgery to capture the phenomena at higher temperatures and present the methods for parameter estimation. Experimental data taken from our surgical trials performed on in vivo porcine liver show that a non-Fourier Maxwell- Cattaneo-type model can be suitable for this application when used in combination with an Arrhenius-type model that approximates the energy dissipation in physical and chemical reactions. The resulting model structure has the advantage of higher accuracy than existing ones, while reducing the computation time required.
KW - electrosurgery
KW - heat conduction
KW - ionic heating
KW - live tissue response parametrization
KW - machine learning
KW - radiofrequency ablation
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U2 - 10.1098/rsif.2023.0420
DO - 10.1098/rsif.2023.0420
M3 - Article
C2 - 38228182
AN - SCOPUS:85182621163
SN - 1742-5689
VL - 21
JO - Journal of the Royal Society Interface
JF - Journal of the Royal Society Interface
IS - 210
M1 - 20230420
ER -