A continuum thermomechanical model for the electrosurgery of soft hydrated tissues using a moving electrode

Abstract

Electrosurgical radio-frequency heating of tissue is widely applied in minimally invasive surgical procedures to dissect tissue with simultaneous coagulation to obtain hemostasis. The tissue effect depends on the cumulative heating that occurs in the vicinity of the moving blade electrode. In this work, a continuum thermomechanical model based on mixture theory, which accounts for the multiphase nature of soft hydrated tissues and includes transport and evaporation losses, is used to capture the transient heating effect of a moving electrode. The model takes into account the dependence of electrical conductivity and the evaporation rate on the water content in the tissue, as it changes in response to heating. Temperature prediction is validated with mean experimental temperature measured during in situ experiments performed on porcine liver tissue at different power settings of the electrosurgical unit. The model is shown to closely capture the temperature variation in the tissue for three distinct scenarios; with no visible cutting or coagulation damage at a low 10 W power setting, with coagulation damage but no tissue cutting at an intermediate power setting of 25 W, and with both coagulation and tissue cutting at a higher power setting of 50 W. Furthermore, an Arrhenius model is shown to capture tissue damage observed in the experiments. Increase in applied power was found to correlate with tissue cutting and concentrated damage near the electrode, but had little effect on the observed coagulation damage width. The proposed model provides, for the first time, an accurate tool for predicting temperature rise and evolving damage resulting from a moving electrode in pure-cut electrosurgery.

Keywords:

• Electrosurgery
• multiphysics modeling
• mixture theory
• tissue damage

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

The authors gratefully acknowledge the support of this work through National Institute of Health (NIH) grants NIH/NIBIB R01EB010037, R01EB009362, R01EB005807, R01EB014305, R01HL119248, and R44OD018334.