Background – Successful treatment of large tumours in the head and neck (H&N)
region is challenging and side-effects of current treatments are severe . Hyperthermia (HT) doubles the effectiveness of radiotherapy for many tumour sites, without increasing side-effects . During my PhD period, I clinically introduced HT for H&N tumours by combining electromagnetic phased-array technology and detailed patient-specific HT treatment planning (HTP). Controlled delivery of heat further requires online dosimetry; ideally done using a dense, three-dimensional, grid of thermometers. Unfortunately, placement of these thermometers in the H&N region can be problematic so we must rely
on sparse thermometry data.
Approach – In this project, I propose to merge our worldwide unique HTP capabilities with the sparse thermometry data from the clinic. A pre-treatment HTP calibration cycle at low power is introduced for matching power absorption predictions to temperature increase measurements. Because this cycle can be performed at low power, the possibility arises to calibrate with multiple different distributions: increasing the quantity of measurement data and improving the quality of calibration. For each distribution, the difference between measurements and simulations is minimized and the required correction matrixes are combined into one single calibration matrix. This innovative
method enables correction of translation errors from planning to clinic and makes accurate on-line HTP guided optimization possible. The versatile methodology will also be applied for calibration using non-invasive temperature measurements inside the patient by MRI, and/or electric field measurements outside the patient.
Implications – The proposed research will lead to an accurate match between predicted and measured heat delivery. Combined with my novel dynamic steering techniques, this leads to target-conformal heating: potentially the gateway to simultaneous application of radiation and heat, dramatically increasing the thermal enhancement factor from 1.5 to 5 . Finally, this project will enable me to start a research line on clinical HT technology.