PFI-TT: A Smart Bipolar Surgical Device for Electrosurgery

University Of Texas At Austin, Austin TX

Investigators

Abstract

The broader impact/commercial potential of this Partnerships for Innovation - Technology Translation (PFI-TT) project is to advance surgical technology by introducing sensing, detection, monitoring, and artificial intelligence in surgical tools to reduce risk, improve patient outcome, and create economic opportunities for the U.S. manufacturing industry. Specifically, the proposed project will develop a smart surgical device for electrosurgery that is a widely used for hemostasis in many major surgical procedures. Despite its advantages for fast operation, shorter recovery time, and suitability for minimal invasive operations, the electrosurgery technology suffers from major challenges such as tissue sticking, charring, surgical smoke generation, peripheral thermal damage, and seal failure that could lead to life-threatening rebleeding. The proposed smart electrosurgical technology will help eliminate rebleeding, ensure a healthy working environment, and save hospitals hundreds of millions of dollars annually. The proposed project will facilitate partnership among academic researchers, device designers, manufacturers, commercialization experts, and end users. It will provide real-world training opportunities, both technical and entrepreneurial, to students of diverse backgrounds and promote the startup of companies for job creation. The proposed project will develop an innovative acoustic sensing and monitoring method to predict the formation of reliable blood vessel seals, providing quality assurance in electrosurgical procedures. Existing methods to mitigate the risk associated with electrosurgeries include applying non-sticking coating to the electrodes, adding cooling channels to the electrical forceps, and automatically terminating the electrical power based on the tissue impedance change. However, these methods are either cumbersome or unreliable due to the variability of tissue properties. The innovative acoustic sensing technology proposed in this project captures the fundamental physical phenomenon of the electrosurgical process and is not affected by the tissue variability. The proposed research will develop scientific understanding of the relationship between tissue heating and the acoustic signal, use machine learning to predict the size of the heat affected zone (HAZ), and develop a smart electrosurgical device for demonstration. The proposed research will also explore the feasibility of developing a graphene-based acoustic sensor to be integrated with the smart surgical device such that the signal quality can be significantly enhanced. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.