Improvement of the hybrid approach between Monte Carlo simulation and analytical function for calculating microdosimetric probability densities in macroscopic matter.

. Estimation of the probability density of the microdosimetric quantities in macroscopic matter is indispensable for applying the concept of microdosimetry to medical physics and radiological protection. The Particle and Heavy Ion Transport code System (PHITS) enables estimating the microdosimetric probability densities due to its unique hybrid modality between the Monte Carlo and analytical approaches called the microdosimetric function. It can convert the deposition energies calculated by the macroscopic Monte Carlo radiation transport simulation to microdosimetric probability densities in water using an analytical function based on the track-structure simulations.. In this study, we improved this function using the latest track-structure simulation codes implemented in PHITS. The improved function is capable of calculating the probability densities of not only the conventional microdosimetric quantities such as lineal energy but also the number of ionization events occurring in a target site, the so-called ionization cluster size distribution, for arbitrary site diameters from 3 nm to 1m.. The accuracy of the improved function was well verified by comparing the microdosimetric probability densities measured by tissue-equivalent proportional counters with the corresponding data calculated in this study. Test calculations for clonogenic cell survival using the improved function coupled with the modified microdosimetric kinetic model suggested a slight increase of its relative biological effectiveness compared with our previous estimations. As a new application of the improved function, we calculated the relative biological effectiveness of the single-strand break and double-strand break yields for proton irradiations using the updated PHITS coupled with the simplified DNA damage estimation model, and confirmed its equivalence in accuracy and its superiority in computational time compared to our previously proposed method based on the track-structure simulation.. From these features, we concluded that the improved function could expand the application fields of PHITS by bridging the gap between microdosimetry and macrodosimetry.