A Monte Carlo-based simulation tool for modeling X-ray computed tomography physics: Application to electron beam CT

Purpose. The CT image is a representation of the patient's anatomy as measured in terms of such physical characteristics as density, electron density, and atomic number. The process of sampling the patient's molecular composition with x-ray is subject to varied physical effects that violate the assumptions behind CT imaging and degrade the ability of the image data to accurately quantify the tissues of the body. We sought to develop a Monte Carlo based modeling tool capable of simulating a CT scanner at full clinical resolution. Selective control of specific physical effects would allow us to assess their impact on the reconstructed CT image.; Methods & materials. A Monte Carlo radiation transport code (MCNP4b) is used to track photons in an Electron Beam CT geometry, through simulated geometric and anthropomorphic phantoms, to a detector array for final reconstruction into images. The native code was modified to incorporate a phase space model of the X-Ray source and a unique two dimensional photon tally necessary to track all source and detector positions for reconstruction. A series of validation steps was conducted to establish the performance of our virtual simulation tool in terms of image noise, energy sensitivity, and selective control of scatter and beam hardening. Final validation was performed through comparison of simulated images against actual scans of a test phantom. Then, simulations were performed of an ideal, non-existent scenario: CT image reconstructions performed in the absence of scatter.; Results. Progressive experimental steps demonstrated that our modeling tool behaved in a predictable fashion. Final validation of simulation against actual scans showed no statistical difference in reconstructed images. Simulations with scatter removed from our virtual scanner showed significant improvement over normal scatter images.; Conclusion. Creation of a Monte Carlo based virtual CT allows us to simulate actual scan geometry as well as a variety of patient and scanner physical conditions that can impact the CT image. Such a tool could be used to generate image corrections or as a CT design tool. The accuracy of the tool is limited only by the level of detail of the created model and the absolute number of Monte Carlo particle histories run.