Electrosurgical Jaw Temperature Feedback for Thermal Spread Control
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Solution Overview
Problem
Existing energy-based surgical forceps face challenges in minimizing thermal spread to adjacent tissues during tissue treatment, as the application of energy to grasp and treat tissue often leads to unintended heating of external tissues.
Innovation Solution
An electrosurgical system with an end effector assembly, temperature sensors, and a controller that predicts and controls thermal spread by adjusting energy supply based on real-time temperature data and machine learning algorithms to maintain thermal spread within acceptable limits.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If electrosurgical energy is supplied to tissue grasped between jaw members to treat tissue, then tissue treatment effectiveness is improved, but thermal spread to adjacent tissues increases
Solution Approach 1:
The system incorporates temperature sensors that continuously monitor tissue temperature during electrosurgical energy delivery. The controller receives real-time temperature data and uses it to dynamically adjust energy supply parameters, creating a closed-loop feedback system that prevents thermal spread while maintaining effective tissue treatment
Solution Approach 2:
The system dynamically adjusts energy delivery parameters (power, duration, pulse patterns) based on real-time temperature measurements and machine learning predictions. This dynamic adaptation allows the system to optimize treatment effectiveness while preventing thermal damage to adjacent tissues throughout the procedure
2Object-affected harmful factors
If real-time temperature monitoring and thermal spread prediction are implemented, then thermal spread control is improved, but device complexity increases
Solution Approach 1:
The controller performs multiple functions: it controls energy delivery, processes temperature sensor data, runs machine learning algorithms for thermal spread prediction, and adjusts energy parameters in real-time. By consolidating these functions into a single integrated controller, the system achieves sophisticated thermal management without proportionally increasing overall device complexity
Solution Approach 2:
The machine learning model is trained on historical temperature and energy delivery data to automatically predict thermal spread patterns. The system self-optimizes its control strategy without requiring manual intervention or complex external control systems, reducing the burden on device architecture
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Effectively minimizes unintended thermal spread to adjacent tissues by dynamically controlling energy delivery, preventing tissue damage and ensuring precise tissue treatment.
Implementation Method 1
Energy-based forceps utilize both mechanical clamping action and energy, e.g., monopolar Radio Frequency (RF), bipolar RF, microwave, ultrasonic, light, thermal, or other suitable energy, to heat tissue
Implementation Method 2
The at least one temperature sensor is associated with the end effector assembly... configured to receive sensed temperature data therefrom
Data Source
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AI summary
An electrosurgical system includes an end effector assembly including first and second jaw members each defining an electrically-conductive tissue-contacting surface. At least one of the jaw members is movable between spaced-apart and approximated positions for grasping tissue between the tissue-contacting surfaces. At least one temperature sensor is associated with the end effector assembly. An electrosurgical generator is configured to supply electrosurgical energy for treating tissue grasped between the tissue-contacting surfaces. The generator is configured to receive sensed temperature data from the temperature sensor(s) and includes a controller configured, in real time, to control the supply of energy to tissue, predict thermal spread beyond the first and second jaw members based at least on the sensed temperature data, and modify, where it is determined that the predicted thermal spread is above a threshold thermal spread, the supply of energy to tissue to inhibit realization of the predicted thermal spread.