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Understanding Tissue Response to RF Energy Delivery

At MedRes, we are currently engaged in an R&D project where we use radiofrequency energy delivery to tissues to achieve immediate adhesion, followed by healing response. As it can be immediately appreciated, different tissues react differently to the same type of energy delivery, and the same tissue will react differently to changes in energy delivery. This means that in order to be successful, we need to be able to 1) characterize the tissue we are working with and 2) optimize energy delivery to that specific tissue in order to achieve the desired type of adhesion.


All of this requires sophisticated sensing in the current, experimental period, as well as in a clinical grade tissue adhesion system. As is usually the case, no commercial technology is available to us to conduct our experiments and therefore we need to create our own advanced measurement system to gain a deeper understanding of tissue response to radiofrequency energy delivery.


Our measurement system is designed the quantitatively characterize the tissue before, during and after RF treatment. For our experiments, we have selected RF generators that output energy with our target electrical attributes, such as the desired ranges of frequency and power. While the generators’ technical boundaries are known, the exact amount of energy absorbed by the tissue under various circumstances remains unclear. This necessitated the design of a test instrument that allows us to deliver energy at various intensities, and in different time patterns, allowing us to learn about tissue response based on the data captured. Other physical aspects of our treatment, like force exertion on tissue, tissue temperature, electrode spacing, etc. are also measured. Past research highlighted specific values and ranges of importance, leading to the incorporation of stepper motors and force sensors that work in these specific ranges and give us a reasonable starting point for experimentation.


The measurement system is a blend of two core components:


  • Motorized Test Bench: Outfitted with interchangeable linear electrodes and sensors, to measure temperature, distance and force. The motorized test bench serves as the central hub for tissue testing. As the RF treatment progresses, sensors monitor variations in tissue temperature, electrode distances, and the force applied by the electrodes. A 3D printed tissue holder guarantees optimal tissue placement between the electrodes.


  • Control Unit: Integrated hardware on the printed circuit board manages control, seamlessly working alongside the software’s GUI. This interface allows users to adjust a range of parameters for electrode closure, RF treatment modes and electrode opening. This flexibility enables a comprehensive mapping of RF energy delivery and its effects on tissue. Our software serves as a crucial tool for storing and analyzing data generated during measurements. During the measurements, we monitor tissue temperature changes, the number and duration of RF cycles, and tissue impedance variations, etc.


To assess the result, additional tests after RF energy delivery are used, such as a Burst Pressure (BP) test, that gives us quantitative information on the robustness of adhesions. Significant differences among experimental groups are identified through statistical analysis of mmHg values of burst pressure, via variance analysis and post-hoc tests.


To ensure the accuracy and reliability of our system, we perform reference measurements using calibrated tools and a rigorous validation process. Furthermore, we perform regular self-checks, adjusting the frequency as needed. For example, after prolonged use, specific components may undergo shifts or distortions that could potentially impact distance measurements. In such instances, we insert a standard sample between the electrodes to meticulously evaluate and correct any deviations, maintaining the highest level of precision.


We find that carefully design experimental set ups are critical in evaluating various device design during our development process, leading to conclusions about what design directions work and what directions lead to dead ends. We place great emphasis on test system design, automated data capture, and analytics that drive design choices. Other examples of such critical test equipment included rigs to characterize various tissue resectors, optical test beds to understand endoscope performance or slow motion camera systems to help us understand mechanical interactions between devices and tissue.