Minimally Invasive Live Tissue High-Fidelity Thermophysical Modeling Using Real-Time Thermography.

Area of Science:

• Biomedical Engineering
• Thermodynamics
• Surgical Technology

Background:

• Accurate real-time tissue characterization is crucial for predicting thermal damage during electrosurgery.
• Existing models often fail to account for the finite thermal propagation time in live tissues, especially at high probe speeds.

Purpose of the Study:

• To develop and validate a novel thermodynamic parameter estimation framework for live tissue.
• To enable real-time, damage-conscious planning of electrosurgical procedures through accurate thermal modeling.

Main Methods:

• A novel framework for real-time estimation of thermodynamic parameters (thermal diffusivity, relaxation time, heat source model).
• Utilizes thermographer feedback, power level, and electrosurgical pencil position for high-fidelity tissue-probe interaction modeling.
• Employs a controlled hyperbolic thermodynamics model accounting for finite thermal propagation time.

Main Results:

• The framework successfully estimates key thermodynamic parameters in real-time.
• Validation with simulated porcine muscle and in vivo liver tissue demonstrated high-fidelity, real-time adaptable thermodynamic response modeling.
• Parameterization of the Maxwell-Cattaneo model showed superior accuracy compared to existing methods.

Conclusions:

• The proposed framework offers a significant advancement in real-time thermodynamic modeling of live tissue during electrosurgery.
• This minimally invasive, in situ method enhances the prediction of thermal damage and facilitates safer surgical interventions.
• The study highlights differences in thermodynamic properties between live and dead tissues.