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Reply to ‘Comment on “Experimental verification of ion stopping power prediction from dual energy CT data in tissue surrogates”’
This content has been downloaded from IOPscience. Please scroll down to see the full text. 2014 Phys. Med. Biol. 59 7085 (http://iopscience.iop.org/0031-9155/59/22/7085) View the table of contents for this issue, or go to the journal homepage for more Download details: IP Address: 132.239.1.231 This content was downloaded on 25/05/2017 at 18:17 Please note that terms and conditions apply.
You may also be interested in: Experimental verification of ion stopping power prediction from dual energy CT data in tissue surrogates Paolo Farace Experimental verification of ion stopping power prediction from dual energy CT data in tissue surrogates Nora Hünemohr, Bernhard Krauss, Christoph Tremmel et al. Range prediction for tissue mixtures based on dual-energy CT Christian Möhler, Patrick Wohlfahrt, Christian Richter et al. A stoichiometric calibration method for dual energy computed tomography Alexandra E Bourque, Jean-François Carrier and Hugo Bouchard A general method to derive tissue parameters for Monte Carlo dose calculation with multi-energy CT Arthur Lalonde and Hugo Bouchard Modeling of body tissues for Monte Carlo simulation of radiotherapy treatments planned with conventional x-ray CT systems Nobuyuki Kanematsu, Taku Inaniwa and Minoru Nakao
Institute of Physics and Engineering in Medicine Phys. Med. Biol. 59 (2014) 7085–7087
Physics in Medicine & Biology doi:10.1088/0031-9155/59/22/7085
Reply
Reply to ‘Comment on “Experimental verification of ion stopping power prediction from dual energy CT data in tissue surrogates”’ Nora Hünemohr, Nina Niebuhr and Steffen Greilich German Cancer Research Center (DKFZ), Division of Medical Physics in Radiation Oncology (E040), Im Neuenheimer Feld 280, D-69120 Heidelberg, Germany E-mail: [email protected] Received 8 August 2014, revised 3 September 2014 Accepted for publication 5 September 2014 Published 31 October 2014
Keywords: CT calibration, stopping power ratio, ion therapy (Some figures may appear in colour only in the online journal) We read the comment by Farace with great interest. We acknowledge the accuracy of their results and the simplification offered by not explicitly taking the Zeff information into account for the SPR prediction. We nevertheless believe that the separation of Z-dependency in photon attenuation and determination of electron density are major benefits of using the dual energy CT (DECT) technology for proton- and ion beam treatment planning. Even if the electron density represents the most important tissue parameter with respect to stopping power, we would like to point out that there are tissues having the same electron density but expressing different effective atomic numbers and vice versa (see ‘mammary gland 2’ and ‘urine’ in (Hünemohr et al 2014)). These differences are large enough to be differentiated by DECT (Mahnken et al 2009) and Zeff proved to be a proxy for the I-value (Yang et al 2010) (in contrast of using a Hounsfield unit). Despite the ln I in the Bethe equation, the available information on Zeff represents a step towards higher accuracy in stopping power prediction for these tissues, not to mention its value for Monte Carlo based dose calculation algorithms and related topics (Landry et al 2013), and should not be discarded. Furthermore, we agree the relation between Zeff and I is far from trivial and influenced by at least three factors: (a) the relation of I-value and atomic number itself (ICRU Report 49 1951), (b) the relation of I-value and Zeff for compounds on an atomic level and (c) the relation of I-value and Zeff for tissue mixtures. When a tissue is considered to be a compound consisting of base components, ln I is found to depend linearly on Zeff with the slope being determined by the base components according to (a) and (b). This is especially the case for the soft and bony tissue from (Schneider et al 2000) (figure 1) whose compositions are interpolated using base 0031-9155/14/227085+3$33.00 © 2014 Institute of Physics and Engineering in Medicine Printed in the UK & the USA
7085
Reply
Phys. Med. Biol. 59 (2014) 7085
Figure 1. ln I dependence on effective atomic number for the materials shown in the
original article. Additionally, reference data of aqueous solutions of NaOH and NaCl (diamonds and stars) (table 1) and tissue mixtures (circles) covering the intermediate Zeff range are show.
Table 1. Elemental composition, I-value and effective atomic number of seven aque-
ous solutions of sodium chloride and sodium hydroxide (Niebuhr 2012). Zeff values were determined using a Siemens Somatom Definition Flash following the procedure described in the original article and show excellent agreement with reference values. Reference I-values were calculated with Bragg’s additivity rule (ICRU Report 49 1951, Bragg and Kleeman 1905), reference Zeff were calculated with the exponent m = 3.1.
Solution/ element
H
O
Na
Cl
Reference I-value [eV]
Reference Measured Zeff Measured Zeff Zeff 80/140 Sn kV 100/140 Sn kV
1.3% NaCl 4% NaCl 7.1% NaCl 10.7% NaCl 14.8% NaCl 8.9% NaOH 27.8% NaOH
11.05 10.74 10.40 9.99 9.53 10.42 8.78
87.65 85.26 82.50 79.31 75.67 84.47 75.24
0.51 1.57 2.79 4.21 5.82 5.12 15.98
0.79 2.43 4.31 6.49 8.98 0.00 0.00
76.04 77.56 79.36 81.53 84.09 78.50 85.91
7.66 8.07 8.50 8.94 9.41 7.70 8.19
7.65 8.08 8.53 8.98 9.45 7.70 8.22
7.62 8.06 8.48 8.97 9.44 7.65 8.17
components like water, lipid, protein, carbohydrate, minerals and ash (Woodard and White 1986). In (Hünemohr et al 2014) the linear behavior of the calcium and phosphorus weight for bony tissue taken from the literature is depicted. We found the same to be true also for the intermediate range of effective atomic numbers when studying aqueous solutions of sodium (Z = 11) and chloride (Z = 17) (figure 1, table 1). 7086
Reply
Phys. Med. Biol. 59 (2014) 7085
Commonly tabulated, homogeneous tissues do not express effective atomic numbers in the range of Zeff = 8 to 10 (Yang et al 2010). In CT data, however, those values are naturally present since finite voxel sizes can include any mixture of tissues. The most common is assumed to contain bony and soft tissues (depicted for two examples in figure 1). It is not sufficiently known yet how tissue mixtures are represented in the intermediate Zeff range. We therefore believe that the Zeff from DECT has its justification in a research context to foster and support the validation of simplifications for later use in clinical routine. References Bragg W H and Kleeman R 1905 On the alpha particles of radium, and their loss of range in passing through various atoms and molecules Phil. Mag. 10 318 ICRU Report 49 1951 Stopping Power and Ranges for Protons and Alpha Particles (Bethesda, MD: International Commission on Radiation Units and Measurements) Hünemohr N, Paganetti H, Greilich S, Jäkel O and Seco J 2014 Tissue decomposition from dual energy CT data for MC based dose calculation in particle therapy Med. Phys. 41 061714 Landry G, Parodi K, Wildberger J E and Verhaegen F 2013 Deriving concentrations of oxygen and carbon in human tissues using single-and dual-energy CT for ion therapy applications Phys. Med. Biol. 58 5029 Mahnken A H, Stanzel S and Heismann B 2009 Spectral rZ-projection method for characterization of body fluids in computed tomography: ex vivo experiments Acad. Radiol. 16 763–9 Niebuhr N 2012 Gel-based multimodality (CT/MR) phantoms for ion radiotherapy Bachelor Thesis, Heidelberg University Schneider W, Bortfeld T and Schlegel W 2000 Correlation between CT numbers and tissue parameters needed for Monte Carlo simulations of clinical dose distributions Phys. Med. Biol. 45 459–78 Woodard H Q and White D R 1986 The composition of body tissues Br. J. Radiol. 59 1209–18 Yang M, Virshu G, Clayton J, Zhu X R, Mohan R and Dong L 2010 Theoretical variance analysis of single- and dual-energy computed tomography methods for calculating proton stopping power ratios of biological tissues Phys. Med. Biol. 55 1343–62
7087
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My IOPscience
Reply to ‘Comment on “Experimental verification of ion stopping power prediction from dual energy CT data in tissue surrogates”’
This content has been downloaded from IOPscience. Please scroll down to see the full text. 2014 Phys. Med. Biol. 59 7085 (http://iopscience.iop.org/0031-9155/59/22/7085) View the table of contents for this issue, or go to the journal homepage for more Download details: IP Address: 132.239.1.231 This content was downloaded on 25/05/2017 at 18:17 Please note that terms and conditions apply.
You may also be interested in: Experimental verification of ion stopping power prediction from dual energy CT data in tissue surrogates Paolo Farace Experimental verification of ion stopping power prediction from dual energy CT data in tissue surrogates Nora Hünemohr, Bernhard Krauss, Christoph Tremmel et al. Range prediction for tissue mixtures based on dual-energy CT Christian Möhler, Patrick Wohlfahrt, Christian Richter et al. A stoichiometric calibration method for dual energy computed tomography Alexandra E Bourque, Jean-François Carrier and Hugo Bouchard A general method to derive tissue parameters for Monte Carlo dose calculation with multi-energy CT Arthur Lalonde and Hugo Bouchard Modeling of body tissues for Monte Carlo simulation of radiotherapy treatments planned with conventional x-ray CT systems Nobuyuki Kanematsu, Taku Inaniwa and Minoru Nakao
Institute of Physics and Engineering in Medicine Phys. Med. Biol. 59 (2014) 7085–7087
Physics in Medicine & Biology doi:10.1088/0031-9155/59/22/7085
Reply
Reply to ‘Comment on “Experimental verification of ion stopping power prediction from dual energy CT data in tissue surrogates”’ Nora Hünemohr, Nina Niebuhr and Steffen Greilich German Cancer Research Center (DKFZ), Division of Medical Physics in Radiation Oncology (E040), Im Neuenheimer Feld 280, D-69120 Heidelberg, Germany E-mail: [email protected] Received 8 August 2014, revised 3 September 2014 Accepted for publication 5 September 2014 Published 31 October 2014
Keywords: CT calibration, stopping power ratio, ion therapy (Some figures may appear in colour only in the online journal) We read the comment by Farace with great interest. We acknowledge the accuracy of their results and the simplification offered by not explicitly taking the Zeff information into account for the SPR prediction. We nevertheless believe that the separation of Z-dependency in photon attenuation and determination of electron density are major benefits of using the dual energy CT (DECT) technology for proton- and ion beam treatment planning. Even if the electron density represents the most important tissue parameter with respect to stopping power, we would like to point out that there are tissues having the same electron density but expressing different effective atomic numbers and vice versa (see ‘mammary gland 2’ and ‘urine’ in (Hünemohr et al 2014)). These differences are large enough to be differentiated by DECT (Mahnken et al 2009) and Zeff proved to be a proxy for the I-value (Yang et al 2010) (in contrast of using a Hounsfield unit). Despite the ln I in the Bethe equation, the available information on Zeff represents a step towards higher accuracy in stopping power prediction for these tissues, not to mention its value for Monte Carlo based dose calculation algorithms and related topics (Landry et al 2013), and should not be discarded. Furthermore, we agree the relation between Zeff and I is far from trivial and influenced by at least three factors: (a) the relation of I-value and atomic number itself (ICRU Report 49 1951), (b) the relation of I-value and Zeff for compounds on an atomic level and (c) the relation of I-value and Zeff for tissue mixtures. When a tissue is considered to be a compound consisting of base components, ln I is found to depend linearly on Zeff with the slope being determined by the base components according to (a) and (b). This is especially the case for the soft and bony tissue from (Schneider et al 2000) (figure 1) whose compositions are interpolated using base 0031-9155/14/227085+3$33.00 © 2014 Institute of Physics and Engineering in Medicine Printed in the UK & the USA
7085
Reply
Phys. Med. Biol. 59 (2014) 7085
Figure 1. ln I dependence on effective atomic number for the materials shown in the
original article. Additionally, reference data of aqueous solutions of NaOH and NaCl (diamonds and stars) (table 1) and tissue mixtures (circles) covering the intermediate Zeff range are show.
Table 1. Elemental composition, I-value and effective atomic number of seven aque-
ous solutions of sodium chloride and sodium hydroxide (Niebuhr 2012). Zeff values were determined using a Siemens Somatom Definition Flash following the procedure described in the original article and show excellent agreement with reference values. Reference I-values were calculated with Bragg’s additivity rule (ICRU Report 49 1951, Bragg and Kleeman 1905), reference Zeff were calculated with the exponent m = 3.1.
Solution/ element
H
O
Na
Cl
Reference I-value [eV]
Reference Measured Zeff Measured Zeff Zeff 80/140 Sn kV 100/140 Sn kV
1.3% NaCl 4% NaCl 7.1% NaCl 10.7% NaCl 14.8% NaCl 8.9% NaOH 27.8% NaOH
11.05 10.74 10.40 9.99 9.53 10.42 8.78
87.65 85.26 82.50 79.31 75.67 84.47 75.24
0.51 1.57 2.79 4.21 5.82 5.12 15.98
0.79 2.43 4.31 6.49 8.98 0.00 0.00
76.04 77.56 79.36 81.53 84.09 78.50 85.91
7.66 8.07 8.50 8.94 9.41 7.70 8.19
7.65 8.08 8.53 8.98 9.45 7.70 8.22
7.62 8.06 8.48 8.97 9.44 7.65 8.17
components like water, lipid, protein, carbohydrate, minerals and ash (Woodard and White 1986). In (Hünemohr et al 2014) the linear behavior of the calcium and phosphorus weight for bony tissue taken from the literature is depicted. We found the same to be true also for the intermediate range of effective atomic numbers when studying aqueous solutions of sodium (Z = 11) and chloride (Z = 17) (figure 1, table 1). 7086
Reply
Phys. Med. Biol. 59 (2014) 7085
Commonly tabulated, homogeneous tissues do not express effective atomic numbers in the range of Zeff = 8 to 10 (Yang et al 2010). In CT data, however, those values are naturally present since finite voxel sizes can include any mixture of tissues. The most common is assumed to contain bony and soft tissues (depicted for two examples in figure 1). It is not sufficiently known yet how tissue mixtures are represented in the intermediate Zeff range. We therefore believe that the Zeff from DECT has its justification in a research context to foster and support the validation of simplifications for later use in clinical routine. References Bragg W H and Kleeman R 1905 On the alpha particles of radium, and their loss of range in passing through various atoms and molecules Phil. Mag. 10 318 ICRU Report 49 1951 Stopping Power and Ranges for Protons and Alpha Particles (Bethesda, MD: International Commission on Radiation Units and Measurements) Hünemohr N, Paganetti H, Greilich S, Jäkel O and Seco J 2014 Tissue decomposition from dual energy CT data for MC based dose calculation in particle therapy Med. Phys. 41 061714 Landry G, Parodi K, Wildberger J E and Verhaegen F 2013 Deriving concentrations of oxygen and carbon in human tissues using single-and dual-energy CT for ion therapy applications Phys. Med. Biol. 58 5029 Mahnken A H, Stanzel S and Heismann B 2009 Spectral rZ-projection method for characterization of body fluids in computed tomography: ex vivo experiments Acad. Radiol. 16 763–9 Niebuhr N 2012 Gel-based multimodality (CT/MR) phantoms for ion radiotherapy Bachelor Thesis, Heidelberg University Schneider W, Bortfeld T and Schlegel W 2000 Correlation between CT numbers and tissue parameters needed for Monte Carlo simulations of clinical dose distributions Phys. Med. Biol. 45 459–78 Woodard H Q and White D R 1986 The composition of body tissues Br. J. Radiol. 59 1209–18 Yang M, Virshu G, Clayton J, Zhu X R, Mohan R and Dong L 2010 Theoretical variance analysis of single- and dual-energy computed tomography methods for calculating proton stopping power ratios of biological tissues Phys. Med. Biol. 55 1343–62
7087
