Electrosurgical Tissue Parameter Estimation via Temperature Sensing
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Solution Overview
Problem
Current surgical devices lack accurate methods to estimate tissue mass and thermal resistance, leading to inefficiencies in electrosurgical procedures, as they rely on impedance measurements which are not reliable for controlling energy delivery and can result in over or under-treatment of tissue.
Innovation Solution
The system estimates tissue mass and thermal resistance using temperature sensors and microprocessors to generate control signals for the electrosurgical generator, allowing for precise control of energy delivery based on real-time tissue parameters.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If impedance measurements are used to control energy delivery, then the device can operate with simple control mechanisms, but the measurement precision is insufficient leading to unreliable tissue parameter estimation
Solution Approach 1:
The patent transitions from measuring electrical impedance to measuring temperature as the primary parameter for tissue characterization. Temperature measurements provide more direct and accurate information about tissue mass and thermal resistance, enabling better energy delivery control without requiring complex impedance analysis algorithms
Solution Approach 2:
The patent replaces electrical measurement methods (impedance) with thermal measurement methods (temperature sensing). This substitution provides more reliable tissue parameter estimation because temperature directly reflects the tissue's thermal properties and mass, whereas impedance measurements are indirect and less reliable
2Manufacturing precision
If energy delivery is controlled based on impedance, then the system can operate with simple algorithms, but the treatment precision deteriorates causing over or under-treatment
Solution Approach 1:
The patent implements a feedback control system where temperature measurements are continuously monitored and used to adjust energy delivery in real-time. This feedback mechanism enables precise control of the tissue treatment process, preventing both over-treatment and under-treatment by dynamically adapting energy delivery to actual tissue conditions
Solution Approach 2:
The patent employs dynamic control algorithms that adapt energy delivery parameters based on real-time temperature measurements. The control system dynamically adjusts power levels, pulse durations, and treatment patterns to match the actual thermal state of the tissue, achieving high treatment precision without requiring overly complex predetermined protocols
3Measurement precision
If temperature sensors are added to measure tissue parameters, then measurement precision improves, but device complexity increases due to additional sensors and processing
Solution Approach 1:
The patent designs the temperature sensing system to serve multiple functions: measuring tissue mass, determining thermal resistance, monitoring treatment progress, and controlling energy delivery. This multi-functionality reduces the need for separate measurement systems and minimizes overall device complexity while achieving high measurement precision
Solution Approach 2:
The temperature measurements obtained during normal treatment operation are used to automatically determine tissue parameters and adjust treatment parameters without requiring separate calibration procedures or additional measurement steps. The system self-calibrates and self-adjusts based on the temperature data collected during treatment, reducing operational complexity
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
This approach enables more accurate and controlled tissue treatment, preventing over-cooking or under-treatment by using estimated tissue mass and thermal resistance to adjust energy levels, thereby improving the efficacy and safety of electrosurgical procedures.
Implementation Method 1
The system estimates tissue mass and thermal resistance using temperature sensors and microprocessors
Implementation Method 2
The tissue's impedance converts the electrical energy (also referred to as electrosurgical energy) associated with the AC into heat, which causes the tissue temperature to rise
Data Source
AI summary
Systems and methods for estimating tissue parameters, including mass of tissue to be treated and a thermal resistance scale factor between the tissue and an electrode of an energy delivery device, are disclosed. The method includes sensing tissue temperatures, estimating a mass of the tissue and a thermal resistance scale factor between the tissue and an electrode, and controlling an electrosurgical generator based on the estimated mass and the estimated thermal resistance scale factor. The method may be performed iteratively and non-iteratively. The iterative method may employ a gradient descent algorithm that iteratively adds a derivative step to the estimates of the mass and thermal resistance scale factor until a condition is met. The non-iterative method includes selecting maximum and minimum temperature differences and estimating the mass and the thermal resistance scale factor based on a predetermined reduction point from the maximum temperature difference to the minimum temperature difference.