Step response model and real-time prediction of temperature fields in laser irradiated biological tissues

Laser-induced thermal therapy (LITT) is a promising minimally invasive oncology treatment. Formulating an appropriate thermal therapy scheme is key to ensure successful treatment. The temperature prediction of biological tissue is critical to the evaluation and optimization of thermotherapy scheme. In this work, a temperature prediction model based on step response is established to predict the transient temperature field of biological tissues in real time. Based on the bioheat transfer equation, the step response function model of laser irradiated biological tissues is constructed and the step response matrix is determined offline. On this basis, the step response prediction model of biological tissue transient temperature field is established using the superposition principle. Further, to address the problem of the large storage capacity of the unit step response matrix of the step response prediction model. A prediction model based on temperature response of representative spatial points is established. The temperature response of a finite set of representative spatial points within the tissue is obtained using the step response model of transient temperature field. Through the weighted synthesis of the finite spatial point set temperature response prediction model, the transient temperature field of bioheat transfer system is predicted in real time. Finally, the reliability of the above step response model is demonstrated by the existing experimental data of laser irradiated biological tissues. Numerical experiments are performed to investigate the prediction of temperature fields in laser irradiated biological tissues. The results show that the online calculation time of the step response prediction model and the prediction model based on temperature response of representative spatial points are less than 2% and 0.4% of the online calculation time of the Pennes heat transfer model, respectively. The maximum error of temperature field prediction is approximately 1 degrees C. In addition, the effects of the number of representative spatial points and laser irradiance form on prediction results are discussed. The results demonstrate the universal applicability of the above prediction models.