Session: 16-01-01: Government Agency Student Poster Competition

Paper Number: 150655

150655 - Bipolar Electrosurgery: Experimentation and Monitoring Algorithm Development 

Bipolar electrosurgery, also known as tissue welding, is an electrosurgical operation that is performed with bipolar forceps, where high-frequency electricity is used to achieve hemostasis, i.e., the seal of blood vessels. The advantages of bipolar electrosurgery compared to traditional hemostatic procedures include, but are not limited to, less bleeding, shorter post-surgery recovery time, and suitability for laparoscopic surgery. Despite all the advantages, there is a lack of reliable monitoring methods to indicate whether acceptable hemostasis has been achieved and when the machine-supplied power should be terminated. Monitoring the bipolar tissue hemostasis process initially relied on visual inspection by the surgeon, but the surgeon's view of the weld site is often limited by the laparoscope when performing minimally invasive surgeries. The weld site can also be easily buried in bodily fluids and smoke generated during the surgery. Although machine assisted monitoring methods, including impedance monitoring and temperature sensing, have been developed for improving the quality of bipolar tissue hemostasis, they cannot guarantee the outcome of seal quality. The minimal impedance monitoring method was introduced in the 1980s and has been used as a criterion to stop the machine-supplied power. However, the impedance measurement can be affected by many factors, such as surgical site irrigation, changing displacement between electrodes, and a high power setting during the bipolar tissue hemostasis process. The initial impedance measurement between the electrodes has also been used to determine the amount of energy to be delivered to the tissue. However, these pre-calibrated generators are extremely sensitive to tissue compression, electrode coating, and residual tissue sticking conditions, which strongly affect the measurement. As a result, in current bipolar electrosurgical operations, tissue sticking, charring, and excessive thermal damage still occur, sometimes leading to fatal complications.

The goal of this study is to develop a novel real-time monitoring method for electrosurgical procedures to prevent defects in the electrosurgical process. Using porcine tissue as a surrogate for human tissue, an experimental study is performed to determine the effects of electrosurgery parameters, including power level, time, and compression pressure. Additionally, a thermocouple is implemented to identify the exact temperature that causes tissue discoloration and cauterization. Finally, an acoustic sensor is used to acquire signals of the tissue cauterizing process. Based on experimental results, a real-time monitoring algorithm is developed using the acoustic signal to determine the quality of the electrosurgical process. This study aims to explain the impact of various operational parameters on the efficacy of bipolar electrosurgery. Through methodical incrementation of the machine-supplied bipolar power levels over a wide range of values, the effects of key process parameters are determined. Additionally, the influence of probe compression on the surgical outcome is investigated by implementing different compression levels. These manipulations facilitate an analysis of tissue alteration, focusing on changes in the surface area and the extent of tissue cauterization. The acoustic signal is processed to extract features for a machine learning model development. The findings of this study contribute to a deeper understanding of bipolar electrosurgery’s operational dynamics as well as an algorithm for real-time monitoring, with implications for optimizing electrosurgical technique and patient care in the future.

Presenting Author: Enrique Velasquez Morquecho The University of Texas at Austin

Presenting Author Biography: Currently, I am a Doctoral student conducting research into large-scale manufacturing and application of graphene in the Nano and Biomaterials Manufacturing and Processing Lab in the Walker Department of Mechanical Engineering in the Cockrell School of Engineering at The University of Texas at Austin.

Authors:

Enrique Velasquez Morquecho The University of Texas at Austin
Hamza Rehman The University of Texas at Austin
Seva Joshi The University of Texas at Austin
Deynna Reyna The University of Texas Rio Grande Valley
Tommy Thompson The University of Texas at Austin
Brian Oak The University of Texas at Austin
Wei Li The University of Texas at Austin