Source term prediction in a multilayer tissue during hyperthermia

• Published in: Journal of thermal biology 2015-08, Vol.52, p.187-191
• Main Authors: Baghban, M., Ayani, M.B.
• Format: Article
• Language: English
• Subjects: Algorithms; Blood Physiological Phenomena; Data Interpretation, Statistical; Fever - physiopathology; Heat source; Heating; Heating power; Humans; Hyperthermia; Hyperthermia, Induced - methods; Inverse problem; Multilayer skin tissue; Sequential method; Skin Physiological Phenomena; Skin Temperature - physiology; Temperature; Thermodynamics
• ISSN: 0306-4565; 1879-0992
• DOI: 10.1016/j.jtherbio.2015.07.006

One of the major challenges in the use of hyperthermia to treat cancer is determining the desired heating power of external source in such a way that the thermal injury is confined to the unhealthy tissue. In this study, an inverse method based on the sequential method is proposed to estimate the desired heating power as a function of time for a successful hyperthermia treatment. In order to simulate the measured temperature, the direct problem is solved for a multilayer skin tissue to obtain the temperature data at the skin surface. These data are employed in the inverse problem to estimate the heating power of external source. Two examples are considered to examine the accuracy of the inverse analysis. In addition, the effect of measurement errors is investigated. Results show that the proposed inverse algorithm is able to determine the desired heating power of external source accurately, even in the presence of measurement errors. However, for noisy data, more temperature measurements are required to achieve reliable results. •The unknown time-dependent part of heat source was estimated by using the sequential method from the temperature measurements at one point.•One dimensional Pennes equation was used for modeling the heat transfer in a multilayer tissue, which is stratified into epidermis, dermis, and subcutaneous layers.•Two test cases were presented to examine the ability of the inverse analysis on the estimation.•The effect of measurement errors on the accuracy of the inverse analysis was investigated.