- Email: [email protected]
Abstract ID: 113 Accurate extraction of tissues parameters for Monte Carlo simulations using multi-energy CT
Abstracts / Physica Medica 42 (2017) 1–50
stopping power (Leq), used here as a key physical quantity. For any step, the mean energy loss was simply defined as the product of the step with Leq. Proton inelastic collisions with electrons were added to GPUMCD, a GPU-based Monte Carlo dose calculation code. The proton continuous slowing-down was modelled with the Leq formalism. First, the dose and time impacts of dmax were studied within Geant4. Second, in voxelized geometries, GPUMCD was compared to Geant4 using a high accuracy simulation setup (dmax = 10 lm). The ionization processes alone were activated and the energy straggling was first switched off to validate alone the Leq formalism. The default settings (dmax = 1 mm) in Geant4 led to an error of up to 16.5% in the falloff region, up to 4.8% elsewhere and the computation times were inversely proportional to the maximal step length allowed. Dose differences between Geant4 and GPUMCD were smaller than 0.31% in the Bragg peak for the Leq formalism. GPUMCD 80% falloff positions (R80) matched Geant R80 within 1 lm. With the energy straggling, dose agreements were within 2.7% in the falloff, below 0.83% elsewhere and R80 positions matched within 100 lm. The overall computation times per million transported protons with GPUMCD were 31–173 ms. Under similar conditions, Geant4 computation times were 1.4–20 h. The Leq formalism allows larger steps while preserving the accuracy. It significantly accelerates Monte Carlo proton transport. The Leq formalism constitutes a promising variance reduction technique for computing proton dose distributions in a clinical context. http://dx.doi.org/10.1016/j.ejmp.2017.09.057
Abstract ID: 106 Performance evaluation of two dedicated radioprotective disks in breast intraoperative electron radiotherapy Shiva Ghasemi a,*, Hamid Reza Baghani b,c, Seyed Rabi Mahdavi d, Mohsen Bakhshandeh a, Nahid Nafissi e a
Radiation Technology Department, Shahid Beheshti University of Medical Sciences, Tehran, Iran b Radiation Medicine Department, Shahid Beheshti University, Tehran, Iran c Physics Department, Hakim Sabzevari University, Sabzevar, Iran d Medical Physics Department, Iran University of Medical Sciences, Tehran, Iran e Surgery Department, Iran University of Medical Sciences, Tehran, Iran ⇑ Presenting author. The aim of breast intraoperative electron radiotherapy is to deliver the prescribed dose to the tumor bed during surgery. In this method, sensitive organs such as pectoral muscles, heart and lungs may be exposed to radiation. Therefore, a radioprotective disk is commonly used to protect the underlying healthy tissues. In this study, the performance of two employed radioprotective disks for breast intraoperative radiotherapy in terms of transmission factor (TF) and backscatter factor (BSF) were compared and the optimum disk was introduced. TF and BSF of the disks understudy, first disk consisted of PTFEstainless steel and the second one consisted of PMMA-Copper, were determined through irradiating the disks by LIAC mobile accelerator inside the water phantom and Advanced Markus ion chamber dosimetry. According to the obtained results, the BSF values of second disk in energies of 6, 8, 10 and 12 MeV was 4.5%, 2.8%, 3.8% and 2.9% lower than the first disk, respectively. In addition, the TF values of second disk in energies of 6, 8, 10 and 12 MeV was also 100%, 20%, 60% and 71% lower than the first one, respectively. Based on the results, it can be concluded that the second radioprotective disk (consisted of PMMA and Copper) has the better pro-
23
tecting performance and in addition to the dose uniformity inside the tumor bed, will minimize the received dose to the organs at risk. http://dx.doi.org/10.1016/j.ejmp.2017.09.058
Abstract ID: 108 Study on conformal proton therapy using multileaf collimated beams without tumour-specific range compensators via flat dose-layer stacking Wencheng Shao *, Xiaobin Tang, Changran Geng, Diyun Shu, Chunhui Gong, Yao Ai, Xudong Zhang Nanjing University of Aeronautics and Astronautics, Department of Nuclear Science and Engineering, Nanjing, China ⇑ Presenting author. Purpose. In traditional conformal proton therapy (CPT), proximal dose conformity of tumours is sacrificed for achieving distal dose conformity due to tumour-specific range compensators. This study investigated whether CPT can be realized without tumour-specific range compensators using multileaf-collimated proton beams, and whether range-compensator-free CPT (RCF-CPT) can improve the proximal dose conformity without sacrificing distal conformity. Methods. First, geometric configurations of a virtual multileafcollimator (MLC) and three tumour cases (brain, liver, and prostate) were adopted during Geant4 geometry setup. Second, conformal proton radiation fields were generated for tumour CT slices based on the predesigned MLC using Geant4. Third, flat dose-layers corresponding to these tumour slices were produced using dose patching method in which MLC-collimated subbeams can be utilized to modulate the dose uniformity of these flat dose-layers. Forth, these flat dose-layers were stacked and integrated throughout the tumours for obtaining sufficient tumour dose coverages. Furthermore, dosimetric comparisons between the RCF-CPT and traditional CPT were performed to detail the dosimetric advantages of RCF-CPT. Results. For the three tumour cases, the tumours can be sufficiently covered by 95% relative doses through RCF-CPT, and the maximum tumour doses were smaller than 110% relative doses. Approximately, the proximal doses of RCF-CPT were controlled to 60% relative doses, and 95% dose lines fit with the tumour profiles at proximal tumour regions. Conclusions. Compared with traditional CPT, RCF-CPT can highly enhance the proximal dose conformity of tumours without sacrificing distal conformity. Moreover, the workflows of CPT can be largely simplified based on the range-compensator-free characteristic of RCF-CPT. http://dx.doi.org/10.1016/j.ejmp.2017.09.059
Abstract ID: 113 Accurate extraction of tissues parameters for Monte Carlo simulations using multi-energy CT Arthur Lalonde a,*, Hugo Bouchard a,b a
Universite de Montreal, Departement de Physique, Montreal, Canada Centre de Recherche du Centre Hospitalier de l’Universite de Montreal (CRCHUM), Montreal, Canada ⇑ Presenting author. b
Purpose. Robust tissue characterization is essential for accurate dose calculation[1,2]. In this work, we present a novel method called Bayesian eigentissue decomposition (BETD) [3] to extract Monte Carlo inputs from computed tomography (CT) data having an arbitrary number of energies. Method. Principal component analysis is applied on a reference dataset of human tissues to define eigentissues which are used as
24
Abstracts / Physica Medica 42 (2017) 1–50
an optimal base of materials representing tissue compositions. To ensure robustness against CT noise, the Bayesian estimator is constructed and resolves the maximum a posteriori fraction of eigentissues in each voxel. The performance of the method in deriving proton beam interaction properties is evaluated with dual-energy CT (DECT) data and compared to a state-of-the-art elemental composition parameterization. Comparison is made with several levels of noise and in the presence of statistical variations in tissue composition and density. The performance of the BETD to an arbitrary number of energies is also investigated by simulating CT data with two to five energy bins with equivalent noise levels. Results. Using simulated noise-free CT numbers for 43 reference soft tissues, the BETD and parameterization methods give equivalent results for stopping powers estimation (0.11% and 0.13% respectively). However, when noise and tissue variation are present, the BETD reduces the RMS error on stopping powers from 2.79% for parameterization to 1.88% for the proposed approach. The BETD method also shows potential for using CT with more than 2 energies, where a number of four energy bins is shown to reduce proton beam range uncertainty by a factor of up to 1.5 compared to the parameterization method used with DECT. Conclusion. This work proposes a general approach to determine elemental compositions and density for Monte Carlo inputs using CT data in a clinical context, where noise and tissues variations significantly degrade the performance of currently known methods.
References 1. Paganetti Harald. Phys Med Biol 2012;57(11):R99. 2. Landry Guillaume et al. Med Phys 2010;37(10):5188–98. 3. Lalonde Arthur, Bouchard Hugo. Phys Med Biol 2016;61(22):8044. http://dx.doi.org/10.1016/j.ejmp.2017.09.060
Abstract ID: 114 The impact of dual-energy CT tissue segmentation for low-dose rate prostate brachytherapy Monte Carlo dose calculations Charlotte Remy a,*, Arthur Lalonde b, Hugo Bouchard b,c a
Université de Nantes, Département de Physique, Nantes, France Université de Montréal, Département de Physique, Montréal, Canada c Centre de recherche du CHUM, Montréal, Canada ⇑ Presenting author. b
Purpose. To evaluate the impact of a novel tissue segmentation method based on dual-energy CT (DECT) for low-dose rate (LDR) brachytherapy dose calculations, by comparison with a reference single-energy CT (SECT) segmentation method. Methods. A virtual patient geometry is created using the DICOMRT of a real patient pelvis SECT scan, where known elemental compositions and varying densities are overwritten in each voxel to define a reference phantom. Simulated CT images are generated using XCOM attenuation coefficients, with a 100 kVp spectrum for SECT, and 80 and 140Sn kVp for DECT. Tissue segmentations for Monte Carlo (MC) dose calculations are performed with both SECT and DECT and compared with the reference geometry. For SECT, the method of Schneider et al. [1] is used and for DECT, the eigentissue decomposition of Lalonde & Bouchard [2] used in combination with a Bayesian estimator. A LDR prostate brachytherapy treatment is planned with 125I sources and calculated using the MC code Brachydose for all three cases. Dose distributions and dose-volume histograms (DVH) are compared to the reference dose distribution to investigate the accuracy of the tissue segmentation methods. Results. For noiseless images, DECT-based tissue segmentation outperforms the SECT procedure with a relative dose distribution
root mean square error (RMSE) of 3.08% versus 8.02%, and provides DVH closest to the reference for all tissues. For a medium level of noise (12 HU), Bayesian eigentissue decomposition performs better with a dose calculation RMSE of 6.11% and 8.49% for DECT and SECT, respectively. Both methods yield similar DVHs for the prostate while DECT segmentation remains more accurate for organs at risk. Conclusion. Our study shows that DECT-based tissue segmentation has the potential to provide LDR brachytherapy dose distributions with higher accuracy that conventional SECT in a clinical context, even in the presence of noise.
References 1. Schneider W et al. Correlation between CT numbers and tissue parameters needed for Monte Carlo simulations of clinical dose distributions. Phys Med Biol 2000;45(2):459. 2. Lalonde A, Bouchard H. A general method to derive tissue parameters for Monte Carlo dose calculation with multi-energy CT. Phys Med Biol 2016;61(22):8044. http://dx.doi.org/10.1016/j.ejmp.2017.09.061
Abstract ID: 115 A Monte Carlo-based eigenspectrum decomposition technique for computed tomography Mikaël Simard a,*, Hugo Bouchard a,b a
Université de Montréal, Département de physique, Montréal, Québec, Canada b Centre de recherche du centre hospitaler de l’Université de Montréal, Montréal, Québec, Canada ⇑ Presenting author. Purpose. The characterization of computed tomography (CT) X-ray spectra is important for beam-hardening correction techniques and raw-data reconstruction methods [1,2]. In this work, we propose a novel spectrum estimation approach based on transmission measurements and the use of Monte-Carlo (MC) to generate basis spectra. Methods. The EGSnrc/BEAM MC code is used to generate basis Xray spectra. The XTUBE component module is used to produce bremsstrahlung photon energy spectra from monoenergetic electrons transported through a tungsten target (10°), a beryllium window (1 mm) and additional filtration. To ensure that the modelled spectra cover the features of the unknown spectrum, a total of 40 spectra with various levels of filtration are generated using different thicknesses of aluminum and carbon, ranging from 2 mm to 18 mm. Principal component analysis is performed on the MC-generated model spectra to extract a set of linearly independent basis functions, each called eigenspectrum, which reduces the dimensionality of the problem and allows stable fitting. Transmission measurements of a calibration phantom are simulated using ray-tracing with an 80-kV source and added Poisson noise. The estimated spectrum is expressed as the weighted sum of eigenspectra and reconstructed through a constrained least squares technique. Results. Using 8 eigenspectra, the 80-kV spectrum is reconstructed with a RMS error (RMSE) of 3.8%. The difference between the mean energy of the estimated and true spectrum is 0.01 keV. Reproducing the same methodology for a 140-kV spectrum yields a RMSE of 4.5% and mean energy difference of 0.1 keV. Conclusion. The proposed method is shown promising to accurately characterize X-ray spectra with transmission data. With limited details on the X-ray tube and relying solely on calibration scans, our methodology provides robust spectrum estimation and is promising for reducing the known ill-posedness [3,4] of known transmission-based approaches. Applications of the technique to
stopping power (Leq), used here as a key physical quantity. For any step, the mean energy loss was simply defined as the product of the step with Leq. Proton inelastic collisions with electrons were added to GPUMCD, a GPU-based Monte Carlo dose calculation code. The proton continuous slowing-down was modelled with the Leq formalism. First, the dose and time impacts of dmax were studied within Geant4. Second, in voxelized geometries, GPUMCD was compared to Geant4 using a high accuracy simulation setup (dmax = 10 lm). The ionization processes alone were activated and the energy straggling was first switched off to validate alone the Leq formalism. The default settings (dmax = 1 mm) in Geant4 led to an error of up to 16.5% in the falloff region, up to 4.8% elsewhere and the computation times were inversely proportional to the maximal step length allowed. Dose differences between Geant4 and GPUMCD were smaller than 0.31% in the Bragg peak for the Leq formalism. GPUMCD 80% falloff positions (R80) matched Geant R80 within 1 lm. With the energy straggling, dose agreements were within 2.7% in the falloff, below 0.83% elsewhere and R80 positions matched within 100 lm. The overall computation times per million transported protons with GPUMCD were 31–173 ms. Under similar conditions, Geant4 computation times were 1.4–20 h. The Leq formalism allows larger steps while preserving the accuracy. It significantly accelerates Monte Carlo proton transport. The Leq formalism constitutes a promising variance reduction technique for computing proton dose distributions in a clinical context. http://dx.doi.org/10.1016/j.ejmp.2017.09.057
Abstract ID: 106 Performance evaluation of two dedicated radioprotective disks in breast intraoperative electron radiotherapy Shiva Ghasemi a,*, Hamid Reza Baghani b,c, Seyed Rabi Mahdavi d, Mohsen Bakhshandeh a, Nahid Nafissi e a
Radiation Technology Department, Shahid Beheshti University of Medical Sciences, Tehran, Iran b Radiation Medicine Department, Shahid Beheshti University, Tehran, Iran c Physics Department, Hakim Sabzevari University, Sabzevar, Iran d Medical Physics Department, Iran University of Medical Sciences, Tehran, Iran e Surgery Department, Iran University of Medical Sciences, Tehran, Iran ⇑ Presenting author. The aim of breast intraoperative electron radiotherapy is to deliver the prescribed dose to the tumor bed during surgery. In this method, sensitive organs such as pectoral muscles, heart and lungs may be exposed to radiation. Therefore, a radioprotective disk is commonly used to protect the underlying healthy tissues. In this study, the performance of two employed radioprotective disks for breast intraoperative radiotherapy in terms of transmission factor (TF) and backscatter factor (BSF) were compared and the optimum disk was introduced. TF and BSF of the disks understudy, first disk consisted of PTFEstainless steel and the second one consisted of PMMA-Copper, were determined through irradiating the disks by LIAC mobile accelerator inside the water phantom and Advanced Markus ion chamber dosimetry. According to the obtained results, the BSF values of second disk in energies of 6, 8, 10 and 12 MeV was 4.5%, 2.8%, 3.8% and 2.9% lower than the first disk, respectively. In addition, the TF values of second disk in energies of 6, 8, 10 and 12 MeV was also 100%, 20%, 60% and 71% lower than the first one, respectively. Based on the results, it can be concluded that the second radioprotective disk (consisted of PMMA and Copper) has the better pro-
23
tecting performance and in addition to the dose uniformity inside the tumor bed, will minimize the received dose to the organs at risk. http://dx.doi.org/10.1016/j.ejmp.2017.09.058
Abstract ID: 108 Study on conformal proton therapy using multileaf collimated beams without tumour-specific range compensators via flat dose-layer stacking Wencheng Shao *, Xiaobin Tang, Changran Geng, Diyun Shu, Chunhui Gong, Yao Ai, Xudong Zhang Nanjing University of Aeronautics and Astronautics, Department of Nuclear Science and Engineering, Nanjing, China ⇑ Presenting author. Purpose. In traditional conformal proton therapy (CPT), proximal dose conformity of tumours is sacrificed for achieving distal dose conformity due to tumour-specific range compensators. This study investigated whether CPT can be realized without tumour-specific range compensators using multileaf-collimated proton beams, and whether range-compensator-free CPT (RCF-CPT) can improve the proximal dose conformity without sacrificing distal conformity. Methods. First, geometric configurations of a virtual multileafcollimator (MLC) and three tumour cases (brain, liver, and prostate) were adopted during Geant4 geometry setup. Second, conformal proton radiation fields were generated for tumour CT slices based on the predesigned MLC using Geant4. Third, flat dose-layers corresponding to these tumour slices were produced using dose patching method in which MLC-collimated subbeams can be utilized to modulate the dose uniformity of these flat dose-layers. Forth, these flat dose-layers were stacked and integrated throughout the tumours for obtaining sufficient tumour dose coverages. Furthermore, dosimetric comparisons between the RCF-CPT and traditional CPT were performed to detail the dosimetric advantages of RCF-CPT. Results. For the three tumour cases, the tumours can be sufficiently covered by 95% relative doses through RCF-CPT, and the maximum tumour doses were smaller than 110% relative doses. Approximately, the proximal doses of RCF-CPT were controlled to 60% relative doses, and 95% dose lines fit with the tumour profiles at proximal tumour regions. Conclusions. Compared with traditional CPT, RCF-CPT can highly enhance the proximal dose conformity of tumours without sacrificing distal conformity. Moreover, the workflows of CPT can be largely simplified based on the range-compensator-free characteristic of RCF-CPT. http://dx.doi.org/10.1016/j.ejmp.2017.09.059
Abstract ID: 113 Accurate extraction of tissues parameters for Monte Carlo simulations using multi-energy CT Arthur Lalonde a,*, Hugo Bouchard a,b a
Universite de Montreal, Departement de Physique, Montreal, Canada Centre de Recherche du Centre Hospitalier de l’Universite de Montreal (CRCHUM), Montreal, Canada ⇑ Presenting author. b
Purpose. Robust tissue characterization is essential for accurate dose calculation[1,2]. In this work, we present a novel method called Bayesian eigentissue decomposition (BETD) [3] to extract Monte Carlo inputs from computed tomography (CT) data having an arbitrary number of energies. Method. Principal component analysis is applied on a reference dataset of human tissues to define eigentissues which are used as
24
Abstracts / Physica Medica 42 (2017) 1–50
an optimal base of materials representing tissue compositions. To ensure robustness against CT noise, the Bayesian estimator is constructed and resolves the maximum a posteriori fraction of eigentissues in each voxel. The performance of the method in deriving proton beam interaction properties is evaluated with dual-energy CT (DECT) data and compared to a state-of-the-art elemental composition parameterization. Comparison is made with several levels of noise and in the presence of statistical variations in tissue composition and density. The performance of the BETD to an arbitrary number of energies is also investigated by simulating CT data with two to five energy bins with equivalent noise levels. Results. Using simulated noise-free CT numbers for 43 reference soft tissues, the BETD and parameterization methods give equivalent results for stopping powers estimation (0.11% and 0.13% respectively). However, when noise and tissue variation are present, the BETD reduces the RMS error on stopping powers from 2.79% for parameterization to 1.88% for the proposed approach. The BETD method also shows potential for using CT with more than 2 energies, where a number of four energy bins is shown to reduce proton beam range uncertainty by a factor of up to 1.5 compared to the parameterization method used with DECT. Conclusion. This work proposes a general approach to determine elemental compositions and density for Monte Carlo inputs using CT data in a clinical context, where noise and tissues variations significantly degrade the performance of currently known methods.
References 1. Paganetti Harald. Phys Med Biol 2012;57(11):R99. 2. Landry Guillaume et al. Med Phys 2010;37(10):5188–98. 3. Lalonde Arthur, Bouchard Hugo. Phys Med Biol 2016;61(22):8044. http://dx.doi.org/10.1016/j.ejmp.2017.09.060
Abstract ID: 114 The impact of dual-energy CT tissue segmentation for low-dose rate prostate brachytherapy Monte Carlo dose calculations Charlotte Remy a,*, Arthur Lalonde b, Hugo Bouchard b,c a
Université de Nantes, Département de Physique, Nantes, France Université de Montréal, Département de Physique, Montréal, Canada c Centre de recherche du CHUM, Montréal, Canada ⇑ Presenting author. b
Purpose. To evaluate the impact of a novel tissue segmentation method based on dual-energy CT (DECT) for low-dose rate (LDR) brachytherapy dose calculations, by comparison with a reference single-energy CT (SECT) segmentation method. Methods. A virtual patient geometry is created using the DICOMRT of a real patient pelvis SECT scan, where known elemental compositions and varying densities are overwritten in each voxel to define a reference phantom. Simulated CT images are generated using XCOM attenuation coefficients, with a 100 kVp spectrum for SECT, and 80 and 140Sn kVp for DECT. Tissue segmentations for Monte Carlo (MC) dose calculations are performed with both SECT and DECT and compared with the reference geometry. For SECT, the method of Schneider et al. [1] is used and for DECT, the eigentissue decomposition of Lalonde & Bouchard [2] used in combination with a Bayesian estimator. A LDR prostate brachytherapy treatment is planned with 125I sources and calculated using the MC code Brachydose for all three cases. Dose distributions and dose-volume histograms (DVH) are compared to the reference dose distribution to investigate the accuracy of the tissue segmentation methods. Results. For noiseless images, DECT-based tissue segmentation outperforms the SECT procedure with a relative dose distribution
root mean square error (RMSE) of 3.08% versus 8.02%, and provides DVH closest to the reference for all tissues. For a medium level of noise (12 HU), Bayesian eigentissue decomposition performs better with a dose calculation RMSE of 6.11% and 8.49% for DECT and SECT, respectively. Both methods yield similar DVHs for the prostate while DECT segmentation remains more accurate for organs at risk. Conclusion. Our study shows that DECT-based tissue segmentation has the potential to provide LDR brachytherapy dose distributions with higher accuracy that conventional SECT in a clinical context, even in the presence of noise.
References 1. Schneider W et al. Correlation between CT numbers and tissue parameters needed for Monte Carlo simulations of clinical dose distributions. Phys Med Biol 2000;45(2):459. 2. Lalonde A, Bouchard H. A general method to derive tissue parameters for Monte Carlo dose calculation with multi-energy CT. Phys Med Biol 2016;61(22):8044. http://dx.doi.org/10.1016/j.ejmp.2017.09.061
Abstract ID: 115 A Monte Carlo-based eigenspectrum decomposition technique for computed tomography Mikaël Simard a,*, Hugo Bouchard a,b a
Université de Montréal, Département de physique, Montréal, Québec, Canada b Centre de recherche du centre hospitaler de l’Université de Montréal, Montréal, Québec, Canada ⇑ Presenting author. Purpose. The characterization of computed tomography (CT) X-ray spectra is important for beam-hardening correction techniques and raw-data reconstruction methods [1,2]. In this work, we propose a novel spectrum estimation approach based on transmission measurements and the use of Monte-Carlo (MC) to generate basis spectra. Methods. The EGSnrc/BEAM MC code is used to generate basis Xray spectra. The XTUBE component module is used to produce bremsstrahlung photon energy spectra from monoenergetic electrons transported through a tungsten target (10°), a beryllium window (1 mm) and additional filtration. To ensure that the modelled spectra cover the features of the unknown spectrum, a total of 40 spectra with various levels of filtration are generated using different thicknesses of aluminum and carbon, ranging from 2 mm to 18 mm. Principal component analysis is performed on the MC-generated model spectra to extract a set of linearly independent basis functions, each called eigenspectrum, which reduces the dimensionality of the problem and allows stable fitting. Transmission measurements of a calibration phantom are simulated using ray-tracing with an 80-kV source and added Poisson noise. The estimated spectrum is expressed as the weighted sum of eigenspectra and reconstructed through a constrained least squares technique. Results. Using 8 eigenspectra, the 80-kV spectrum is reconstructed with a RMS error (RMSE) of 3.8%. The difference between the mean energy of the estimated and true spectrum is 0.01 keV. Reproducing the same methodology for a 140-kV spectrum yields a RMSE of 4.5% and mean energy difference of 0.1 keV. Conclusion. The proposed method is shown promising to accurately characterize X-ray spectra with transmission data. With limited details on the X-ray tube and relying solely on calibration scans, our methodology provides robust spectrum estimation and is promising for reducing the known ill-posedness [3,4] of known transmission-based approaches. Applications of the technique to