Current status and new horizons in Monte Carlo simulation of X-ray CT scanners

Abstract

With the advent of powerful computers and parallel processing including Grid technology, the use of Monte Carlo (MC) techniques for radiation transport simulation has become the most popular method for modeling radiological imaging systems and particularly X-ray computed tomography (CT). The stochastic nature of involved processes such as X-ray photons generation, interaction with matter and detection makes MC the ideal tool for accurate modeling. MC calculations can be used to assess the impact of different physical design parameters on overall scanner performance, clinical image quality and absorbed dose assessment in CT examinations, which can be difficult or even impossible to estimate by experimental measurements and theoretical analysis. Simulations can also be used to develop and assess correction methods and reconstruction algorithms aiming at improving image quality and quantitative procedures. This paper focuses mainly on recent developments and future trends in X-ray CT MC modeling tools and their areas of application. An overview of existing programs and their useful features will be given together with recent developments in the design of computational anthropomorphic models of the human anatomy. It should be noted that due to limited space, the references contained herein are for illustrative purposes and are not inclusive; no implication that those chosen are better than others not mentioned is intended.

Multilayer imaging and compositional analysis of human male breast by laser reflectometry and Monte Carlo simulation

“…The reflectance images of the three detector probes help to evaluate the spread of the cancer deep into the tissues similar to that as observed in subjects after frostbite [27]. The placement of detectors above the surface could further be optimized by Monte Carlo simulation similar to as carried out for the CT [38].…”

Monte Carlo-based assessment of the trade-off between spatial resolution, field-of-view and scattered radiation in the variable resolution X-ray CT scanner

“…In this work, we investigate the influence of magnification optimization on a onedimensional VRX CT scanner. The spatial resolution, FOV and scatter-to-primary ratio were evaluated for both fixed and optimized magnifications using Monte Carlo simulations [8]. In our previous study [6], we evaluated the trade-off between spatial resolution and transaxial FOV of the scanner as a function of system magnification.…”

A Monte Carlo software bench for simulation of spectral k-edge CT imaging: Initial results

“…It is used to calculate energy deposition from photons (or electrons) in different parts of the body, thus enabling radiotherapy to estimate the dose distribution at a particular target area for cancer treatment planning [14]. In recent years, MC simulations gained in popularity to simulate photon transport in x-ray imaging, with the main purpose of image quality assessment and new detector configuration development [15]. With accurate modeling of the underlying physics and the incorporation of appropriate cross section data, MC methods provide in-depth assessment and accurate means of predicting radiation transport inside materials with complex geometries [16].…”