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Research Papers

Waveform-Dependent Electrosurgical Effects on Soft Hydrated Tissues

[+] Author and Article Information
Wafaa Karaki, Carlos A. Lopez, Rahul, Diana-Andra Borca-Tasciuc

Center for Modeling, Simulation and Imaging
in Medicine,
Rensselaer Polytechnic Institute,
Troy, NY 12180

Suvranu De

Center for Modeling, Simulation and Imaging
in Medicine,
Rensselaer Polytechnic Institute,
Troy, NY 12180
e-mail: des@rpi.edu

1Corresponding author.

Manuscript received June 11, 2018; final manuscript received February 12, 2019; published online March 25, 2019. Assoc. Editor: Ram Devireddy.

J Biomech Eng 141(5), 051003 (Mar 25, 2019) (14 pages) Paper No: BIO-18-1275; doi: 10.1115/1.4042898 History: Received June 11, 2018; Revised February 12, 2019

Electrosurgical procedures are ubiquitously used in surgery. The commonly used power modes, including the coagulation and blend modes, utilize nonsinusoidal or modulated current waveforms. For the same power setting, the coagulation, blend, and pure cutting modes have different heating and thermal damage outcomes due to the frequency dependence of electrical conductivity of soft hydrated tissues. In this paper, we propose a multiphysics model of soft tissues to account for the effects of multifrequency electrosurgical power modes within the framework of a continuum thermomechanical model based on mixture theory. Electrical and frequency spectrum results from different power modes at low- and high-power settings are presented. Model predictions are compared with in vivo electrosurgical heating experiments on porcine liver tissue. The accuracy of the model in predicting experimentally observed temperature profiles is found to be overall greater when frequency-dependence is included. An Arrhenius type model indicates that more tissue damage is correlated with larger duty cycles in multifrequency modes.

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Figures

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Fig. 1

Summary of the waveform, duty cycle, and modulation frequency of different electrosurgical power modes (top: pure cut, middle: blend, and bottom: coagulation)

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Fig. 2

Schematic of tissue domain and boundary

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Fig. 3

Variation of electrical conductivity of liver tissue (a) with frequency at body temperature and (b) with temperature at different frequencies

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Fig. 4

Variation of the scaled model of electrical conductivity se,n with frequency and temperature

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Fig. 5

Mesh and boundary conditions of the finite element model of electrosurgical heating of liver

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Fig. 6

Voltage and current waveforms measured at 10 W for (a) blend cut, (b) standard coagulation, and (c) spray coagulation power modes. Corresponding Fourier coefficient single-sided amplitude spectrum for 10 W (d) blend cut, (e) standard coagulation, and (f) spray coagulation.

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Fig. 7

Fourier coefficient single-sided amplitude spectrum at 50W for (a) blend cut, (b) standard coagulation, and (c) spray coagulation

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Fig. 8

Variation of mean temperature for in vivo electrosurgical heating at 10 W (solid line) with multifrequency (MF) model (dashed line) and single-frequency (SF) model at 400 kHz (dash-dot line) with radial distance for (a) blend cut, (b) standard coagulation, (c) spray coagulation, and with time for (d) blend cut, (e) standard coagulation, and (f) spray coagulation

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Fig. 9

Variation of mean temperature for in vivo electrosurgical heating at 50 W (solid line) with frequency-dependent waveform model (dashed line) and 400 kHz model (dash-dot line) with radial distance for (a) blend cut, (b) standard coagulation, (c) spray coagulation, and with time for (d) blend cut, (e) standard coagulation, and (f) spray coagulation

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Fig. 10

Damage distribution in the tissue near the electrode after 2 s of heating at 10 W for (a) blend cut, (b) standard coagulation, and (c) spray coagulation

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