Open AccessDesign of a Monte Carlo model based on dual-source computed tomography (DSCT) scanners for dose and image quality assessment using the Monte Carlo N-Particle (MCNP5) code
Author(s) -
Stefania Chantzi,
Emmanouil Papanastasiou,
Christina Athanasopoulou,
Elisavet Molyvda-Athanasopoulou,
Panagiotis D. Bamidis,
Αναστάσιος Σιούντας
Publication year - 2020
Publication title -
polish journal of medical physics and engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.199
H-Index - 5
eISSN - 1898-0309
pISSN - 1425-4689
DOI - 10.2478/pjmpe-2020-0002
Subject(s) - monte carlo method , scanner , image quality , computer science , image resolution , dosimetry , projection (relational algebra) , tomography , collimator , medical physics , algorithm , nuclear medicine , physics , optics , computer vision , artificial intelligence , mathematics , image (mathematics) , medicine , statistics
The purpose of this work was to develop and validate a Monte Carlo model for a Dual Source Computed Tomography (DSCT) scanner based on the Monte Carlo N-particle radiation transport computer code (MCNP5). The geometry of the Siemens Somatom Definition CT scanner was modeled, taking into consideration the x-ray spectrum, bowtie filter, collimator, and detector system. The accuracy of the simulation from the dosimetry point of view was tested by calculating the Computed Tomography Dose Index (CTDI) values. Furthermore, typical quality assurance phantoms were modeled in order to assess the imaging aspects of the simulation. Simulated projection data were processed, using the MATLAB software, in order to reconstruct slices, using a Filtered Back Projection algorithm. CTDI, image noise, CT-number linearity, spatial and low contrast resolution were calculated using the simulated test phantoms. The results were compared using several published values including IMPACT, NIST and actual measurements. Bowtie filter shapes are in agreement with those theoretically expected. Results show that low contrast and spatial resolution are comparable with expected ones, taking into consideration the relatively limited number of events used for the simulation. The differences between simulated and nominal CT-number values were small. The present attempt to simulate a DSCT scanner could provide a powerful tool for dose assessment and support the training of clinical scientists in the imaging performance characteristics of Computed Tomography scanners.