Tissue decomposition from dual energy CT data for MC based dose calculation in particle therapy

Purpose: 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. Methods: The relative electron density ϱe and effective atomic number Zeff are calculated for 71 tabulated tissue...

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Hauptverfasser: Hünemohr, Nora (VerfasserIn) , Paganetti, Harald (VerfasserIn) , Greilich, Steffen (VerfasserIn) , Jäkel, Oliver (VerfasserIn) , Seco, Joao (VerfasserIn)
Dokumenttyp: Article (Journal)
Sprache:Englisch
Veröffentlicht: 23 May 2014
In: Medical physics
Year: 2014, Jahrgang: 41, Heft: 6
ISSN:2473-4209
DOI:10.1118/1.4875976
Online-Zugang:Verlag, lizenzpflichtig, Volltext: https://doi.org/10.1118/1.4875976
Verlag, lizenzpflichtig, Volltext: https://aapm.onlinelibrary.wiley.com/doi/abs/10.1118/1.4875976
Volltext
Verfasserangaben:Nora Hünemohr, Harald Paganetti, Steffen Greilich, Oliver Jäkel, Joao Seco

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520 |a Purpose: 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. Methods: The relative electron density ϱe and effective atomic number Zeff are calculated for 71 tabulated tissue compositions. For MC simulations, the mass density is derived via one linear fit in the ϱe that covers the entire range of tissue compositions (except lung tissue). Elemental mass fractions are predicted from the ϱe and the Zeff 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. Results: Mean deviations to ground truth in mass density predictions could be reduced for soft tissue from (0.5±0.6)% (SECT) to (0.2±0.2)% with the DECT method. Maximum SPR deviations could be reduced significantly for soft tissue from 3.1% (SECT) to 0.7% (DECT) and for bone tissue from 0.8% to 0.1%. MeanI-value deviations could be reduced for soft tissue from (1.1±1.4%, SECT) to (0.4±0.3%) with the presented method. Predictions of elemental composition were improved for every element. Mean and maximum deviations from ground truth of all elemental mass fractions could be reduced by at least a half with DECT compared to SECT (except soft tissue hydrogen and nitrogen where the reduction was slightly smaller). The carbon and oxygen mass fraction predictions profit especially from the DECT information. Dose studies showed that most of the 12 selected tissues would profit significantly (up to 2.2%) from DECT material decomposition with no noise present. The ϱe associated with an absolute noise of ±0.01 and Zeff associated with an absolute noise of ±0.2 resulted in ±10% standard variation in the carbon and oxygen mass fraction prediction. Conclusions: Accurate stopping power prediction is mainly determined by the correct mass density prediction. Theoretical improvements in range predictions with DECT data in the order of 0.1%-2.1% were observed. Further work is needed to quantify the potential improvements from DECT compared to SECT in measured image data associated with artifacts and noise. 
650 4 |a Applications 
650 4 |a Biological material 
650 4 |a bone 
650 4 |a Calibrating of instruments or apparatus 
650 4 |a calibration 
650 4 |a Carbon 
650 4 |a Collisional energy loss 
650 4 |a composition 
650 4 |a Computed tomography 
650 4 |a Computerised tomographs 
650 4 |a computerised tomography 
650 4 |a Digital computing or data processing equipment or methods 
650 4 |a Dose-volume analysis 
650 4 |a dosimetry 
650 4 |a Dosimetry 
650 4 |a Dosimetry/exposure assessment 
650 4 |a dual energy CT 
650 4 |a e.g. blood 
650 4 |a e.g. from bit-mapped to bit-mapped creating a similar image 
650 4 |a Haemocytometers 
650 4 |a Image data processing or generation 
650 4 |a image denoising 
650 4 |a Image enhancement or restoration 
650 4 |a in general 
650 4 |a Lungs 
650 4 |a Medical image noise 
650 4 |a medical image processing 
650 4 |a Monte Carlo 
650 4 |a Monte Carlo methods 
650 4 |a Noise 
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650 4 |a radiation therapy 
650 4 |a Radiation therapy 
650 4 |a range uncertainty 
650 4 |a Scintigraphy 
650 4 |a specially adapted for specific applications 
650 4 |a stoichiometric calibration 
650 4 |a Testing or calibrating of apparatus or arrangements provided for in groups G01D1/00 to G01D15/00 
650 4 |a Tissues 
650 4 |a urine 
650 4 |a Verification 
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