@article{oai:repo.qst.go.jp:00047596,
 author = {Kanematsu, Nobuyuki and Inaniwa, Taku and Nakao, Minoru and 兼松 伸幸 and 稲庭 拓 and 中尾 稔},
 issue = {13},
 journal = {Physics in Medicine and Biology},
 month = {Jun},
 note = {In the conventional procedure for accurate Monte Carlo simulation of radiotherapy, a CT number given to each pixel of a patient image is directly converted to mass density and elemental composition using their respective functions that have been calibrated speci cally for the relevant x-ray CT system. We propose an alternative approach that is a conversion in two steps: the  rst from CT number to density and the second from density to composition. Based on the latest compilation of standard tissues for reference adult male and female phantoms, we sorted the standard tissues into groups by mass density and de ned the representative tissues by averaging the material properties per group. With these representative tissues, we formulated polyline relations between mass density and each of the following; electron density, stopping-power ratio and elemental densities. We also revised a procedure of stoichiometric calibration for CT-number conversion and demonstrated the two-step conversion method for a theoretically emulated CT system with hypothetical 80 keV photons. For the standard tissues, high correlation was generally observed between mass density and the other densities excluding those of C and O for the light spongiosa tissues between 1.0 g cm−3 and 1.1 g cm−3 occupying 1% of the human body mass. The polylines  tted to the dominant tissues were generally consistent with similar formulations in the literature. The two-step conversion procedure was demonstrated to be practical and will potentially facilitate Monte Carlo simulation for treatment planning and for retrospective analysis of treatment plans with little impact on the management of planning CT systems.},
 pages = {5037--5050},
 title = {Modeling of body tissues for Monte Carlo simulation of radiotherapy treatments planned with conventional x-ray CT systems},
 volume = {61},
 year = {2016}
}