Alejandro Bertolet

Space- and Time-Defined Monte Carlo Dosimetry Explains Ovarian Cancer Cell Viability in Targeted α-Particle Therapy With Astatine 211-ParaThanatrace

Radiopharmaceutical therapy (RPT) aims to irradiate tumors using antibodies or small molecules chelated with radioisotopes that target tumor cells. The biological response resulting from the complex interplay between radioisotope decay and cell binding processes is not yet fully understood. Because dose, including its spatiotemporal pattern, strongly correlates with ionizing radiation effects, detailed dosimetry is essential to predict biological responses. This study introduces TOol for PArticle Simulation (TOPAS)-RPT, a Monte Carlo platform for stochastic and spatiotemporal heterogeneous radiation exposures that models the interplay of radioisotope decay and radioligand-receptor binding. We implemented new models within the TOPAS Monte Carlo platform to enable the dynamic simulation of RPT exposures. Simulations were discretized over time in a series of independent runs. Binding kinetics were implemented using a compartmental model with dynamic populations, updating the abundance and distribution of the isotopes at every time step. In this work, TOPAS-RPT was applied to replicate in vitro viability experiments on ovarian cancer cells (SKOV3 and PEO1) treated under different conditions with astatine 211-ParaThanatrace ([ We used the proposed TOPAS-RPT to perform a dose-viability analysis. In PEO1 cells, we observed a consistent dose-viability response when cells were exposed to [ The characterized time- and space-structure of the absorbed dose needs to be accounted for to explain variabilities in radiosensitivity to RPT exposures with diverse binding properties and radiation emissions.