12. Main Tables: Stopping Powers, Ranges, and Radiation Yields

Berger, M. J.; Inokuti, Mitio; Anderson, H. H.; Bichsel, H.; Dennis, J. A.; Powers, D.; Seltzer, S. M.; Turner, James

doi:10.1093/jicru_os19.2.55

Cited by 5 publications

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“…The relative stopping power was computed for a proton kinetic energy of 100 MeV and a mean excitation energy of water of I w = 78 eV, based on the latest ICRU 90 recommendations (Seltzer et al 2016). For biological tissues and tissue-substitutes, the I-value was calculated using the Bragg additivity rule and the I-values of the atomic constituents in solid state (Berger et al 1984). Finally, the CT numbers based on two x-ray spectra at 80 and 140 kVp (van der Heyden et al 2018) were calculated using (A.15) and (A.16)-the energy response of the radiation detector was assumed to be constant.…”

Section: Theoretical Evaluation Of Tissue-substitutesmentioning

confidence: 99%

“…The proton electronic stopping power of a given element or mixture may be expressed as (Berger et al 1993)…”

Section: Appendix a Theorymentioning

confidence: 99%

“…where e is the charge of the electron, m e c 2 is its rest energy, β is the velocity of the proton in units of speed of light and L(β) is the stopping number. Using Bethe's formulation of the stopping number (Berger et al 1993), and neglecting both shell and density effect corrections, the proton electronic stopping power relative to the one of water-i.e. the relative stopping power (RSP)-may be approximated as (Schneider et al 1996) .19) where I is the mean excitation energy of the medium.…”

Section: Appendix a Theorymentioning

confidence: 99%

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Revisiting the single-energy CT calibration for proton therapy treatment planning: a critical look at the stoichiometric method

2018

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Despite extensive research in dual-energy computed tomography (CT), single-energy CT (SECT) is still the standard imaging modality in proton therapy treatment planning and, in this context, the stoichiometric calibration method is considered to be the most accurate to establish a relationship between CT numbers and proton stopping power. This work revisits the SECT calibration for proton therapy treatment planning, with special emphasis on the stoichiometric method. Three different sets of tissue-substitutes of known elemental composition (Gammex, CIRS and Catphan) were scanned with the same scanning protocol. A stoichiometric fit was performed for each set of tissue-substitutes. Based on that, the CT number, relative electron density and relative proton stopping power were calculated for ICRU 46 biological tissues and the different sets of tissue-substitutes. Despite common belief, it was found that the stoichiometric fit depends on the elemental composition of the tissue-substitutes used in the calibration, leading to differences in relative stopping power up to 3.5% for cortical bone. In addition, according to Rutherford et al (1976 Neuroradiology 11 15-21) parametrization of the atomic cross-section, CT numbers of Gammex tissue-substitutes and ICRU 46 biological tissues were found to be similar within the whole energy range relevant to computed tomography. Consequently, it was found that, for Gammex tissue-substitutes, the CT calibration curve resulting from the stoichiometric method agrees with that obtained by simple interpolation of experimental data. In conclusion, the stoichiometric method for SECT calibration seems to depend on the tissue-substitutes used for calibration-which could be regarded as an additional source of uncertainty in proton range for bone tissues. Furthermore, Gammex tissue-substitutes appear to be a good representative of biological tissues within the energy range relevant to computed tomography-making the stoichiometric method unnecessary.

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Section: Theoretical Evaluation Of Tissue-substitutesmentioning

confidence: 99%

“…The proton electronic stopping power of a given element or mixture may be expressed as (Berger et al 1993)…”

Section: Appendix a Theorymentioning

confidence: 99%

Section: Appendix a Theorymentioning

confidence: 99%

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Revisiting the single-energy CT calibration for proton therapy treatment planning: a critical look at the stoichiometric method

2018

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“…Calculation of I for materials used Bragg additivity and bound-state elemental I-values 33 and EAN was calculated using Mayneord's power law (see e.g. Ödén et al 31 ) with an exponent of 3.1.…”

Section: 22mentioning

confidence: 99%

Stopping‐power ratio estimation for proton radiotherapy using dual‐energy computed tomography and prior‐image constrained denoising

2022

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Background: Dual-energy computed tomography (DECT) is a promising technique for estimating stopping-power ratio (SPR) for proton therapy planning. It is known, however, that deriving electron density (ED) and effective atomic number (EAN) from DECT data can cause noise amplification in the resulting SPR images. This can negate the benefits of DECT. Purpose: This work introduces a new algorithm for estimating SPR from DECT with noise suppression, using a pair of CT scans with spectral separation. The method is demonstrated using phantom measurements. Materials and methods: An iterative algorithm is presented, reconstructing ED and EAN with noise suppression, based on Prior Image Constrained Denoising (PIC-D). The algorithm is tested using a Siemens Definition AS+ CT scanner (Siemens Healthcare, Forchheim, Germany). Three phantoms are investigated: a calibration phantom (CIRS 062M), a QA phantom (CATPHAN 700), and an anthropomorphic head phantom (CIRS 731-HN). A task-transfer function (TTF) and the noise power spectrum are derived from SPR images of the QA phantom for the evaluation of image quality. Comparisons of accuracy and noise for ED, EAN, and SPR are made for various versions of the algorithm in comparison to a solution based on Siemens syngo.via Rho/Z software and the current clinical standard of a single-energy CT stoichiometric calibration. A gamma analysis is also applied to the SPR images of the head phantom and water-equivalent distance (WED) is evaluated in a treatment planning system for a proton treatment field. Results:The algorithm is effective at suppressing noise in both ED and EAN and hence also SPR. The noise is tunable to a level equivalent to or lower than that of the syngo.via Rho/Z software. The spatial resolution (10% and 50% frequencies in the TTF) does not degrade even for the highest noise suppression investigated, although the average spatial frequency of noise does decrease. The PIC-D algorithm showed better accuracy than syngo.via Rho/Z for low density materials. In the calibration phantom, it was superior even when excluding lung substitutes, with root-mean-square deviations for ED and EAN less than 0.3% and 2%, respectively, compared to 0.5% and 3%. In the head phantom, however, the SPR accuracy of the PIC-D algorithm was comparable (excluding sinus tissue) to that derived from syngo.via Rho/Z: less than 1% error for soft tissue, brain, and trabecular bone substitutes and 5-7% for cortical bone, withThis is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

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“…The only free parameter for the stopping power prediction is normally the mean ionization potential (I-value). In the ICRU report 37 [31], an I-value of 57.4 eV was suggested for polyethylene and is also the standard value used by FLUKA. However, this value has no major significance because it is simply the average of two available measurements at the time of the report (52.5 eV [32] and 62.2 eV [33]).…”

Section: Adjustment Of Mean Ionization Potentialmentioning

confidence: 99%

Precise measurement of the Bragg curve for 800 MeV/u ²³⁸U ions stopping in polyethylene and its implications for calculation of heavy ion ranges

et al. 2022

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Stopping power predictions in radiation transport codes are based on the Bethe-Bloch formula and different corrections. For very heavy ions at relativistic energies the available experimental data are scarce and therefore verification of stopping power predictions is only possible to a limited extent. In this work, a full experimental Bragg curve for 800 MeV/u 238U ions stopping in polyethylene is presented. The measurements were conducted at the experimental area Cave A at GSI Helmholtzzentrum für Schwerionenforschung in Darmstadt, Germany. The 800 MeV/u 238U beam was provided by the SIS18 heavy ion synchrotron. The Bragg curve was measured with a setup consisting of a binary range shifter and two large area parallel plate ionization chambers. Complementary Monte Carlo simulations using the FLUKA code were performed and compared with the experimental Bragg curve. The mean ionization potential of polyethylene was fine-tuned to match the measured primary ion range with FLUKA simulations. The impact of the Bloch and Mott corrections to the stopping power calculation were studied by switching them off intentionally in separate simulations. A detailed description of the implementation of the stopping power formulae and the Mott correction in FLUKA is provided. Supplementary data for this article is available online.

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12. Main Tables: Stopping Powers, Ranges, and Radiation Yields

Cited by 5 publications

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Revisiting the single-energy CT calibration for proton therapy treatment planning: a critical look at the stoichiometric method

Revisiting the single-energy CT calibration for proton therapy treatment planning: a critical look at the stoichiometric method

Stopping‐power ratio estimation for proton radiotherapy using dual‐energy computed tomography and prior‐image constrained denoising

Precise measurement of the Bragg curve for 800 MeV/u ²³⁸U ions stopping in polyethylene and its implications for calculation of heavy ion ranges

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12. Main Tables: Stopping Powers, Ranges, and Radiation Yields

Cited by 5 publications

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Revisiting the single-energy CT calibration for proton therapy treatment planning: a critical look at the stoichiometric method

Revisiting the single-energy CT calibration for proton therapy treatment planning: a critical look at the stoichiometric method

Stopping‐power ratio estimation for proton radiotherapy using dual‐energy computed tomography and prior‐image constrained denoising

Precise measurement of the Bragg curve for 800 MeV/u 238U ions stopping in polyethylene and its implications for calculation of heavy ion ranges

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Precise measurement of the Bragg curve for 800 MeV/u ²³⁸U ions stopping in polyethylene and its implications for calculation of heavy ion ranges