title: Tissue segmentation in Monte Carlo treatment planning: a simulation study using dual-energy CT images.
abstract: OBJECTIVE
  Tissue segmentation is an important step in Monte Carlo (MC) dose calculation and is often done uncritically. A new approach to tissue segmentation using dual-energy CT images is studied in this work.
  
  
  METHODS
  A simple MC model of a CT scanner was built and CT images of phantoms with ten tissue-equivalent cylinders were simulated using soft and hard X-ray spectra. The Z and rho(e) of the cylinders were extracted using a formalism based on a parameterization of the linear attenuation coefficient.
  
  
  RESULTS
  It was shown that in order to extract Z and rho(e) with a reasonable accuracy, hard X-ray beams have to be used for scanning. When an additional filtration of 9 mm of aluminium in the CT X-ray beam is used, beam hardening in high density materials is suppressed and the mean errors of the extraction of Z and rho(e) for 10 tissue-equivalent materials in a small tissue-equivalent phantom are 3.7% and 3.1%, respectively.
  
  
  CONCLUSIONS
  MC simulations were used to show that the extraction of Z and rho(e) for a number of tissue-equivalent materials using dual-energy CT images is possible which improves tissue segmentation for Monte Carlo dose calculations, as demonstrated with a 250 kVp photon beam dose calculation.
authors: Medical Physics Unit, Montreal General Hospital, McGill University, Montréal, Québec, Canada.
authors: Magdalena
authors: M
authors: Bazalova
authors: Jean-François
authors: JF
authors: Carrier
authors: Luc
authors: L
authors: Beaulieu
authors: Frank
authors: F
authors: Verhaegen
mesh_terms: D000465:Algorithms; D009010:Monte Carlo Method; D019047:Phantoms, Imaging; D011879:Radiotherapy Dosage; D011880:Radiotherapy Planning, Computer-Assisted / Q000379:methods*; D014057:Tomography, X-Ray Computed