NEURAL NETWORK MODELLING OF CARDIAC DOSE CONVERSION COEFFICIENT FOR ARBITRARY X-RAY SPECTRA

In this article, an approach to compute the dose conversion coefficients (DCCs) is described for the computational voxel phantom 'High-Definition Reference Korean-Man' (HDRK-Man) using artificial neural networks (ANN). For this purpose, the voxel phantom was implemented into the Monte Carlo (MC) transport toolkit GEANT4, and the DCCs for more than 30 tissues and organs, due to a broad parallel beam of monoenergetic photons with energy ranging from 15 to 150 keV by a step of 5 keV, were calculated. To study the influence of patient size on DCC values, DCC calculation was performed, for a representative body size population, using five different sizes covering the range of 80-120 % magnification of the original HDRK-Man. The focus of the present study was on the computation of DCC for the human heart. ANN calculation and MC simulation results were compared, and good agreement was observed showing that ANNs can be used as an efficient tool for modelling DCCs for the computational voxel phantom. ANN approach appears to be a significant advance over the time-consuming MC methods for DCC calculation.