ESTRO 2025 - Abstract Book

S2920

Physics - Dose prediction, optimisation and applications of photon and electron planning

ESTRO 2025

Material/Methods: A hyperthermia treatment plan was retrospectively generated for four H&N cancer patients. We examined the effects of 47 uncertainty parameters, encompassing variations in dielectric and thermal tissue properties of each segmented tissue as well as patient positioning. We modeled the response of the temperature distribution to these parameters using polynomial chaos expansion (PCE). Input uncertainty of the parameters followed Gaussian distributions, with means and standard deviations based on ranges and measurements reported in literature. We extracted metrics about the resulting statistical temperature distributions by evaluating 100,000 random error scenarios via PCE. Results: Uncertainties significantly affected target temperatures, with the 95% confidence interval (CI) of the (minimum temperature in 50% of target volume) averaging 3.07 °C. Figure 1 illustrates a patient-specific example of how the combined uncertainties influence the temperature distribution. Figure 2 illustrates the impact of increasing the positioning uncertainty on the cumulative target temperature-volume histograms (TVH) in combination with tissue property variations, for all four patients.

Figure 1 : (a) Mean, (b) standard deviation, and (c) mean deviation from the nominal treatment plan for temperature distribution, accounting for all uncertainties. Tumor outlined in black.

Figure 2 : TVH for the 95% CI of the target temperature, considering tissue property uncertainties for four patients and increasing positioning uncertainty (legend reports the 95% CI of positioning error).