Simulation of computed tomography (CT) images using a Monte Carlo approach

Heavy ion treatment planning uses an empirical scanner-dependent calibration relation between computed tomography (CT) numbers and ion range. Any deviation in the values of CT numbers will cause a drift in the calibration curve of the CT scanner, which can reduce the accuracy of treatment beam delivery. To reduce uncertainty in the empiri- cal estimation of CT numbers, we developed a simulation that takes into consideration the geometry, composition, and physical process that underlie their measurement. This approach uses Monte Carlo (MC) simulations, followed by a simple filtered back-projection reconstruction. The MC code used is BEAMnrc/EGSnrc. With the manufacturer's permission, we simulated the components (X-ray tube, associated filters and beam shapers) of a Siemens Emotion CT. We then gener- ated an initial beam shape and spectra, and performed further simulations using the phantom with substitutes. We analyzed the resulting phase space file to calculate projections, taking into account the energy response of the CT detectors. Then, we applied a simple reconstruction algorithm to the calculated projections in order to receive the CT image.