Three-Phase-Lag Bio-Heat Transfer Model of Cardiac Ablation

Non-Fourier Bioheat Transfer Analysis in Brain Tissue During Interstitial Laser Ablation: Analysis of Multiple Influential Factors

This work presents the dual-phase lag-based non-Fourier bioheat transfer model of brain tissue subjected to interstitial laser ablation. The finite element method has been utilized to predict the brain tissue's temperature distributions and ablation volumes. A sensitivity analysis has been conducted to quantify the effect of variations in the input laser power, treatment time, laser fiber diameter, laser wavelength, and non-Fourier phase lags. Notably, in this work, the temperature-dependent thermal properties of brain tissue have been considered. The developed model has been validated by comparing the temperature obtained from the numerical and ex vivo brain tissue during interstitial laser ablation. The ex vivo brain model has been further extended to in vivo settings by incorporating the blood perfusion effects. The results of the systematic analysis highlight the importance of considering temperature-dependent thermal properties of the brain tissue, non-Fourier behavior, and microvascular perfusion effects in the computational models for accurate predictions of the treatment outcomes during interstitial laser ablation, thereby minimizing the damage to surrounding healthy tissue. The developed model and parametric analysis reported in this study would assist in a more accurate and precise prediction of the temperature distribution, thus allowing to optimize the thermal dosage during laser therapy in the brain.

Heat transfer analysis for tissue with surface heat flux based on the non-linearized form of the three-phase-lag model

The three-phase-lag model of heat conduction has been proposed for considering thermoelastic effect in medium. The bioheat transfer equations based on Taylor's series approximation of the three-phase-lag model were derived in conjunction with a modified energy conservation equation. For exploring the effect of non-linear expansion in the phase lag times, the Taylor's series of second-order expansion was applied. The resulting equation involves mixed derivative terms and higher-order derivatives of temperature with respect to time. The hybrid application of the Laplace transform method and a modified discretization technique was extended to solve the equations and explore the effect of thermoelasticity on the thermal behavior in living tissue with surface heat flux. The influence of thermoelastic parameters and phase lags on heat transfer in tissue has been investigated. The present results illustrate the thermal response oscillation is excited in medium for the thermoelastic effect, the phase lag times significantly affect the amplitude and frequency of the oscillation, and the expansion order of TPL model evidently affects the predicted temperature.

Temperature Dependence of Thermal Properties of Ex Vivo Porcine Heart and Lung in Hyperthermia and Ablative Temperature Ranges

This work proposes the characterization of the temperature dependence of the thermal properties of heart and lung tissues from room temperature up to > 90 °C. The thermal diffusivity (α), thermal conductivity (k), and volumetric heat capacity (C_v) of ex vivo porcine hearts and deflated lungs were measured with a dual-needle sensor technique. α and k associated with heart tissue remained almost constant until ~ 70 and ~ 80 °C, accordingly. Above ~ 80 °C, a more substantial variation in these thermal properties was registered: at 94 °C, α and k respectively experienced a 2.3- and 1.5- fold increase compared to their nominal values, showing average values of 0.346 mm²/s and 0.828 W/(m·K), accordingly. Conversely, C_v was almost constant until 55 °C and decreased afterward (e.g., C_v = 2.42 MJ/(m³·K) at 94 °C). Concerning the lung tissue, both its α and k were characterized by an exponential increase with temperature, showing a marked increment at supraphysiological and ablative temperatures (at 91 °C, α and k were equal to 2.120 mm²/s and 2.721 W/(m·K), respectively, i.e., 13.7- and 13.1-fold higher compared to their baseline values). Regression analysis was performed to attain the best-fit curves interpolating the measured data, thus providing models of the temperature dependence of the investigated properties. These models can be useful for increasing the accuracy of simulation-based preplanning frameworks of interventional thermal procedures, and the realization of tissue-mimicking materials.