%0 Journal Article
%A Hünemohr, Nora
%A Paganetti, Harald
%A Greilich, Steffen
%A Jäkel, Oliver
%A Seco, Joao
%T Tissue decomposition from dual energy CT data for MC based dose calculation in particle therapy.5
%J Medical physics
%V 41
%N 6
%@ 0094-2405
%C New York, NY
%M DKFZ-2017-02094
%P 061714
%D 2014
%X The authors describe a novel method of predicting mass density and elemental mass fractions of tissues from dual energy CT (DECT) data for Monte Carlo (MC) based dose planning.The relative electron density ϱ(e) and effective atomic number Z(eff) are calculated for 71 tabulated tissue compositions. For MC simulations, the mass density is derived via one linear fit in the ϱ(e) that covers the entire range of tissue compositions (except lung tissue). Elemental mass fractions are predicted from the ϱ(e) and the Z(eff) in combination. Since particle therapy dose planning and verification is especially sensitive to accurate material assignment, differences to the ground truth are further analyzed for mass density, I-value predictions, and stopping power ratios (SPR) for ions. Dose studies with monoenergetic proton and carbon ions in 12 tissues which showed the largest differences of single energy CT (SECT) to DECT are presented with respect to range uncertainties. The standard approach (SECT) and the new DECT approach are compared to reference Bragg peak positions.Mean deviations to ground truth in mass density predictions could be reduced for soft tissue from (0.5±0.6)
%K Protons (NLM Chemicals)
%F PUB:(DE-HGF)16
%9 Journal Article
%$ pmid:24877809
%2 pmc:PMC4032427
%R 10.1118/1.4875976
%U https://inrepo02.dkfz.de/record/125979