Literature DB >> 27782721

A robust empirical parametrization of proton stopping power using dual energy CT.

Vicki T Taasti1, Jørgen B B Petersen1, Ludvig P Muren1, Jesper Thygesen2, David C Hansen1.   

Abstract

PURPOSE: In this study the authors present a new method for estimation of proton stopping power ratios (SPRs) using dual energy CT (DECT), which is robust toward CT noise. The authors propose a parametrization for SPR based directly on the CT numbers in a DECT image set, whereby the intermediate steps of estimating the relative electron density, ρe, and mean excitation energy, I, are avoided.
METHODS: The SPR parametrization proposed in this study is a purely empirical fit based on the theoretical SPR values for a list of 34 reference human tissues. To investigate the SPR estimation made with this new method the authors performed a calibration and an evaluation with the method. The authors initially calculated CT numbers using CT energy spectrum characterization parameters obtained from calibration based on a Gammex 467 electron density calibration phantom. These CT numbers were fitted to the theoretical SPR for the reference human tissues using the new SPR parametrization presented in this study. The method was evaluated based on theoretical CT numbers for the reference human tissues. The root-mean-square error (RMSE) of the SPR and the proton range error from the continuous slowing down approximation were calculated for the reference human tissues. To test the stability of the parametrization the authors varied the density and elemental composition of the reference human tissues and calculated their new SPR estimates. Further, clinically realistic noise values were added to the theoretical CT numbers to investigate how CT noise affected the estimated water equivalent range through 10 cm of the reference human tissues. All results for the new SPR parametrization were compared to the results obtained using two previously published DECT methods for SPR estimation. Comparisons were also made to a single energy CT (SECT) SPR estimation method, the stoichiometric method, which is commonly used in clinical practise for proton therapy treatment planning.
RESULTS: The RMSE for the SPR of the 34 reference human tissues using the new SPR parametrization was 0.12%, compared to 0.19% and 0.28% for the two previously published DECT methods. The SPR parametrization was more stable toward variations of the calcium content in the reference human tissues, but less stable toward density variations and changes to the hydrogen content than the two other DECT methods. When adding noise to the theoretical CT numbers the SPR parametrization gave the lowest water equivalent range errors of all four tested SPR estimation methods (maximum error reduced to 0.4 mm). In all cases tested, the new SPR parametrization outperformed the SECT stoichiometric method.
CONCLUSIONS: The new SPR parametrization gave lower RMSEs than the two other published DECT methods, and was in particular more robust against added noise. The method has potential for reducing range uncertainty margins in treatment planning of proton therapy.

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Year:  2016        PMID: 27782721     DOI: 10.1118/1.4962934

Source DB:  PubMed          Journal:  Med Phys        ISSN: 0094-2405            Impact factor:   4.071


  10 in total

1.  Systematic analysis of the impact of imaging noise on dual-energy CT-based proton stopping power ratio estimation.

Authors:  Hugh H C Lee; Bin Li; Xinhui Duan; Linghong Zhou; Xun Jia; Ming Yang
Journal:  Med Phys       Date:  2019-04-01       Impact factor: 4.071

2.  Theoretical and experimental analysis of photon counting detector CT for proton stopping power prediction.

Authors:  Vicki T Taasti; David C Hansen; Gregory J Michalak; Amanda J Deisher; Jon J Kruse; Ludvig P Muren; Jørgen B B Petersen; Cynthia H McCollough
Journal:  Med Phys       Date:  2018-10-01       Impact factor: 4.071

Review 3.  Status and innovations in pre-treatment CT imaging for proton therapy.

Authors:  Patrick Wohlfahrt; Christian Richter
Journal:  Br J Radiol       Date:  2019-11-11       Impact factor: 3.039

4.  Determination of proton stopping power ratio with dual-energy CT in 3D-printed tissue/air cavity surrogates.

Authors:  Jerimy C Polf; Matthew M Mille; Sina Mossahebi; Haijian Chen; Paul Maggi; Huaiyu Chen-Mayer
Journal:  Med Phys       Date:  2019-06-05       Impact factor: 4.071

5.  The accuracy of helium ion CT based particle therapy range prediction: an experimental study comparing different particle and x-ray CT modalities.

Authors:  L Volz; C-A Collins-Fekete; E Bär; S Brons; C Graeff; R P Johnson; A Runz; C Sarosiek; R W Schulte; J Seco
Journal:  Phys Med Biol       Date:  2021-11-29       Impact factor: 3.609

6.  Improved accuracy of relative electron density and proton stopping power ratio through CycleGAN machine learning.

Authors:  Jessica Scholey; Luciano Vinas; Vasant Kearney; Sue Yom; Peder Eric Zufall Larson; Martina Descovich; Atchar Sudhyadhom
Journal:  Phys Med Biol       Date:  2022-05-02       Impact factor: 4.174

7.  Comprehensive analysis of proton range uncertainties related to stopping-power-ratio estimation using dual-energy CT imaging.

Authors:  B Li; H C Lee; X Duan; C Shen; L Zhou; X Jia; M Yang
Journal:  Phys Med Biol       Date:  2017-08-09       Impact factor: 3.609

8.  MULTI-ENERGY CONE-BEAM CT RECONSTRUCTION WITH A SPATIAL SPECTRAL NONLOCAL MEANS ALGORITHM.

Authors:  Bin Li; Chenyang Shen; Yujie Chi; Ming Yang; Yifei Lou; Linghong Zhou; Xun Jia
Journal:  SIAM J Imaging Sci       Date:  2018-05-08       Impact factor: 2.867

9.  Comparison of single and dual energy CT for stopping power determination in proton therapy of head and neck cancer.

Authors:  Vicki Trier Taasti; Ludvig Paul Muren; Kenneth Jensen; Jørgen Breede Baltzer Petersen; Jesper Thygesen; Anna Tietze; Cai Grau; David Christoffer Hansen
Journal:  Phys Imaging Radiat Oncol       Date:  2018-04-22

10.  Initial Validation of Proton Dose Calculations on SPR Images from DECT in Treatment Planning System.

Authors:  Sina Mossahebi; Pouya Sabouri; Haijian Chen; Michelle Mundis; Matthew O'Neil; Paul Maggi; Jerimy C Polf
Journal:  Int J Part Ther       Date:  2020-11-23
  10 in total

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