title: Dual-energy CT-based material extraction for tissue segmentation in Monte Carlo dose calculations.
abstract: Monte Carlo (MC) dose calculations are performed on patient geometries derived from computed tomography (CT) images. For most available MC codes, the Hounsfield units (HU) in each voxel of a CT image have to be converted into mass density (rho) and material type. This is typically done with a (HU; rho) calibration curve which may lead to mis-assignment of media. In this work, an improved material segmentation using dual-energy CT-based material extraction is presented. For this purpose, the differences in extracted effective atomic numbers Z and the relative electron densities rho(e) of each voxel are used. Dual-energy CT material extraction based on parametrization of the linear attenuation coefficient for 17 tissue-equivalent inserts inside a solid water phantom was done. Scans of the phantom were acquired at 100 kVp and 140 kVp from which Z and rho(e) values of each insert were derived. The mean errors on Z and rho(e) extraction were 2.8% and 1.8%, respectively. Phantom dose calculations were performed for 250 kVp and 18 MV photon beams and an 18 MeV electron beam in the EGSnrc/DOSXYZnrc code. Two material assignments were used: the conventional (HU; rho) and the novel (HU; rho, Z) dual-energy CT tissue segmentation. The dose calculation errors using the conventional tissue segmentation were as high as 17% in a mis-assigned soft bone tissue-equivalent material for the 250 kVp photon beam. Similarly, the errors for the 18 MeV electron beam and the 18 MV photon beam were up to 6% and 3% in some mis-assigned media. The assignment of all tissue-equivalent inserts was accurate using the novel dual-energy CT material assignment. As a result, the dose calculation errors were below 1% in all beam arrangements. Comparable improvement in dose calculation accuracy is expected for human tissues. The dual-energy tissue segmentation offers a significantly higher accuracy compared to the conventional single-energy segmentation.
authors.affiliation: Medical Physics Unit, McGill University, Montreal General Hospital, Montreal, QC, Canada.
authors.forename: Magdalena
authors.initials: M
authors.lastname: Bazalova
authors.forename: Jean-François
authors.initials: JF
authors.lastname: Carrier
authors.forename: Luc
authors.initials: L
authors.lastname: Beaulieu
authors.forename: Frank
authors.initials: F
authors.lastname: Verhaegen
mesh_terms: D000465:Algorithms; D002138:Calibration; D004583:Electrons; D006801:Humans; D007091:Image Processing, Computer-Assisted; D015233:Models, Statistical; D008962:Models, Theoretical; D009010:Monte Carlo Method; D019047:Phantoms, Imaging; D017785:Photons; D011874:Radiometry / Q000295:instrumentation / Q000379:methods*; D015203:Reproducibility of Results; D012984:Software; D015898:Tomography Scanners, X-Ray Computed; D014057:Tomography, X-Ray Computed / Q000379:methods*