CPU-GPU coupling independent reaction times method in NASIC and application in water radiolysis by FLASH irradiation

Abstract

The mechanism of the FLASH effect remains unclear and could be revealed by studying chemical reactions during irradiation. Monte Carlo simulation of the radiolytic species is an effective tool to analyze chemical reactions, but the simulation is limited by computing costs of the step-by-step simulation of radiolytic species, especially when considering beam with complex time structure. The complexity of the time structure of beams from accelerators in FLASH radiotherapy requires a high-performance Monte Carlo code. In this work, we develop a CPU-GPU coupling accelerating code with the independent reaction times (IRT) method to extend the chemical module of our nanodosimetry Monte Carlo code NASIC. Every chemical molecule in the microenvironment contains time information to consider the reactions from different tracks and simulate beams with complex time structures. Performance test shows that our code significantly improved the computing efficiency of the chemical module by four orders of magnitude. Then the code is used to study the oxygen depletion hypothesis in FLASH radiotherapy for different conditions by setting different parameters. The transient oxygen consumption rate values in the water are calculated when the pulses width ranges from 2 ps to 2 μs, the total dose ranges from 0.5 Gy to 100 Gy and the initial oxygen concentration ranges from 0.1% to 21%. The time evolution curves are simulated to study the effect of the time structure of an electron linear accelerator. Results show that the total dose in several microseconds is a better indicator reflecting the radiolytic oxygen consumption rate than the dose rate. The initial oxygen greatly affects the oxygen consumption rate because of the reaction competition. The diffusion of oxygen determined by the physiological parameters is the key factor affecting oxygen depletion during the radiation using electron linear accelerators. Our code provides an efficient tool for simulating water radiolysis in different conditions.