Background and purpose: Hyperthermia treatment planning (HTP) is used in the head and neck region (H&N) for pretreatment optimization, decision making, and real-time HTP-guided adaptive application of hyperthermia. In current clinical practice, HTP is based on power-absorption predictions, but thermal dose-effect relationships advocate its extension to temperature predictions. Exploitation of temperature simulations requires region- and temperature-specific thermal tissue properties due to the strong thermoregulatory response of H&N tissues. The purpose of our work was to develop a technique for patient group-specific optimization of thermal tissue properties based on invasively measured temperatures, and to evaluate the accuracy achievable.
Patients and methods: Data from 17 treated patients were used to optimize the perfusion and thermal conductivity values for the Pennes bioheat equation-based thermal model. A leave-one-out approach was applied to accurately assess the difference between measured and simulated temperature (∆T). The improvement in ∆T for optimized thermal property values was assessed by comparison with the ∆T for values from the literature, i.e., baseline and under thermal stress.
Results: The optimized perfusion and conductivity values of tumor, muscle, and fat led to an improvement in simulation accuracy (∆T: 2.1 ± 1.2 °C) compared with the accuracy for baseline (∆T: 12.7 ± 11.1 °C) or thermal stress (∆T: 4.4 ± 3.5 °C) property values.
Conclusion: The presented technique leads to patient group-specific temperature property values that effectively improve simulation accuracy for the challenging H&N region, thereby making simulations an elegant addition to invasive measurements. The rigorous leave-one-out assessment indicates that improvements in accuracy are required to rely only on temperature-based HTP in the clinic.