title: A bone composition model for Monte Carlo x-ray transport simulations.
abstract: In the megavoltage energy range although the mass attenuation coefficients of different bones do not vary by more than 10%, it has been estimated that a simple tissue model containing a single-bone composition could cause errors of up to 10% in the calculated dose distribution. In the kilovoltage energy range, the variation in mass attenuation coefficients of the bones is several times greater, and the expected error from applying this type of model could be as high as several hundred percent. Based on the observation that the calcium and phosphorus compositions of bones are strongly correlated with the bone density, the authors propose an analytical formulation of bone composition for Monte Carlo computations. Elemental compositions and densities of homogeneous adult human bones from the literature were used as references, from which the calcium and phosphorus compositions were fitted as polynomial functions of bone density and assigned to model bones together with the averaged compositions of other elements. To test this model using the Monte Carlo package DOSXYZnrc, a series of discrete model bones was generated from this formula and the radiation-tissue interaction cross-section data were calculated. The total energy released per unit mass of primary photons (terma) and Monte Carlo calculations performed using this model and the single-bone model were compared, which demonstrated that at kilovoltage energies the discrepancy could be more than 100% in bony dose and 30% in soft tissue dose. Percentage terma computed with the model agrees with that calculated on the published compositions to within 2.2% for kV spectra and 1.5% for MV spectra studied. This new bone model for Monte Carlo dose calculation may be of particular importance for dosimetry of kilovoltage radiation beams as well as for dosimetry of pediatric or animal subjects whose bone composition may differ substantially from that of adult human bones.
authors.affiliation: Department of Radiation Oncology, Stanford University, Stanford, California 94305, USA. huzhou06@stanford.edu
authors.forename: Hu
authors.initials: H
authors.lastname: Zhou
authors.forename: Paul J
authors.initials: PJ
authors.lastname: Keall
authors.forename: Edward E
authors.initials: EE
authors.lastname: Graves
mesh_terms: D000328:Adult; D000465:Algorithms; D000818:Animals; D055592:Biophysical Phenomena; D015519:Bone Density; D001842:Bone and Bones / Q000737:chemistry* / Q000000981:diagnostic imaging*; D002648:Child; D003198:Computer Simulation; D006801:Humans; D051379:Mice; D009010:Monte Carlo Method; D019047:Phantoms, Imaging; D011880:Radiotherapy Planning, Computer-Assisted / Q000706:statistics & numerical data*; D014057:Tomography, X-Ray Computed