Many biomedical applications involve the use of energy deposition into in homogeneous structures, such as laser surgery, cryosurgery, and RF ablation. In many cases, numerous advantages can be realized when the energy source is pulsed. No commercial software package exists to assist clinicians in determining the direction, duration, and magnitude of these energy interventions. In particular, existing predictive tools do not account for the effects associated with the laser interaction with thin tissues. While well-known approximations, such as the Diffusion Model, adequately account for interactions with thick tissue samples, they do not accurately model the effects associated with thin tissues where interactions with boundaries becomes important. Furthermore, when pulsed energy is deposited in tissue at ultra-high frequency, the subsequent conduction in the tissue no longer adheres to Fourier's conduction law, further complicating simulations.
The specific aim of this project is to develop a general, commercial software modeling and simulation environment that will enable accurate assessment of heat transfer for biomedical applications involving energy deposition in tissues across the spectrums of thin to thick tissue layers and ultra-fast to continuous wave lasers, including those situations when non-Fourier heat conduction is important. Our thermal modeling and simulation environment will provide an easy-to-use tool for clinicians and biomedical researchers to plan accurately and understand a wide variety of pulsed and non-pulsed energy deposition-based clinical procedures. In Phase I, we will develop the general framework for a stand-alone software package that will be demonstrated with comparisons to experimental data, analytic solutions, and Monte Carlo simulations. In Phase II, we will develop a complete and robust package with an intuitive graphical user interface, refined models, and greatly expanded property data base developed in conjunction with our collaborators. We will also conduct appropriate experiments and work closely with clinicians to verify the underlying models and numerical schemes and gather additional required material properties.
