Journal Articles
2019
Shoemaker, Tristan; Vuong, Té; Glickman, Harry; Kaifi, Samar; Famulari, Gabriel; Enger, Shirin A.
Dosimetric Considerations for Ytterbium-169, Selenium-75, and Iridium-192 Radioisotopes in High-Dose-Rate Endorectal Brachytherapy Journal Article
In: International Journal of Radiation Oncology, Biology, Physics, vol. 105, no. 4, pp. 875–883, 2019, ISSN: 1879-355X.
Abstract | Links | BibTeX | Tags: Brachytherapy, Femur, Humans, Iridium Radioisotopes, Monte Carlo Method, Organs at Risk, Pelvic Bones, Radioisotopes, Radiotherapy Dosage, Rectal Neoplasms, Rectum, Selenium Radioisotopes, Tomography, Urinary Bladder, X-Ray Computed, Ytterbium
@article{shoemaker_dosimetric_2019,
title = {Dosimetric Considerations for Ytterbium-169, Selenium-75, and Iridium-192 Radioisotopes in High-Dose-Rate Endorectal Brachytherapy},
author = {Tristan Shoemaker and Té Vuong and Harry Glickman and Samar Kaifi and Gabriel Famulari and Shirin A. Enger},
doi = {10.1016/j.ijrobp.2019.07.003},
issn = {1879-355X},
year = {2019},
date = {2019-11-01},
journal = {International Journal of Radiation Oncology, Biology, Physics},
volume = {105},
number = {4},
pages = {875--883},
abstract = {PURPOSE: To investigate differences between prescribed and postimplant calculated dose in 192Ir high-dose-rate endorectal brachytherapy (HDR-EBT) by evaluating dose to clinical target volume (CTV) and organs at risk (OARs) calculated with a Monte Carlo-based dose calculation software, RapidBrachyMC. In addition, dose coverage, conformity, and homogeneity were compared among the radionuclides 192Ir, 75Se, and 169Yb for use in HDR-EBT.
METHODS AND MATERIALS: Postimplant dosimetry was evaluated using 23 computed tomography (CT) images from patients treated with HDR-EBT using the 192Ir microSelectron v2 (Elekta AB, Stockholm, Sweden) source and the Intracavitary Mold Applicator Set (Elekta AB, Stockholm, Sweden), which is a flexible applicator capable of fitting a tungsten rod for OAR shielding. Four tissue segmentation schemes were evaluated: (1) TG-43 formalism, (2) materials and nominal densities assigned to contours of foreign objects, (3) materials and nominal densities assigned to contoured organs in addition to foreign objects, and (4) materials specified as in (3) but with voxel mass densities derived from CT Hounsfield units. Clinical plans optimized for 192Ir were used, with the results for 75Se and 169Yb normalized to the D90 of the 192Ir clinical plan. RESULTS: In comparison to segmentation scheme 4, TG-43-based dosimetry overestimates CTV D90 by 6% (P = .00003), rectum D50 by 24% (P = .00003), and pelvic bone D50 by 5% (P = .00003) for 192Ir. For 169Yb, CTV D90 is overestimated by 17% (P = .00003) and rectum D50 by 39% (P = .00003), and pelvic bone D50 is significantly underestimated by 27% (P = .007). Postimplant dosimetry calculations also showed that a 169Yb source would give 20% (P = .00003) lower rectum V60 and 17% (P = .00008) lower rectum D50.
CONCLUSIONS: Ignoring high-Z materials in dose calculation contributes to inaccuracies that may lead to suboptimal dose optimization and disagreement between prescribed and calculated dose. This is especially important for low-energy radionuclides. Our results also show that with future magnetic resonance imaging-based treatment planning, loss of CT density data will only affect calculated dose in nonbone OARs by 2% or less and bone OARs by 13% or less across all sources if material composition and nominal mass densities are correctly assigned.},
keywords = {Brachytherapy, Femur, Humans, Iridium Radioisotopes, Monte Carlo Method, Organs at Risk, Pelvic Bones, Radioisotopes, Radiotherapy Dosage, Rectal Neoplasms, Rectum, Selenium Radioisotopes, Tomography, Urinary Bladder, X-Ray Computed, Ytterbium},
pubstate = {published},
tppubtype = {article}
}
PURPOSE: To investigate differences between prescribed and postimplant calculated dose in 192Ir high-dose-rate endorectal brachytherapy (HDR-EBT) by evaluating dose to clinical target volume (CTV) and organs at risk (OARs) calculated with a Monte Carlo-based dose calculation software, RapidBrachyMC. In addition, dose coverage, conformity, and homogeneity were compared among the radionuclides 192Ir, 75Se, and 169Yb for use in HDR-EBT.
METHODS AND MATERIALS: Postimplant dosimetry was evaluated using 23 computed tomography (CT) images from patients treated with HDR-EBT using the 192Ir microSelectron v2 (Elekta AB, Stockholm, Sweden) source and the Intracavitary Mold Applicator Set (Elekta AB, Stockholm, Sweden), which is a flexible applicator capable of fitting a tungsten rod for OAR shielding. Four tissue segmentation schemes were evaluated: (1) TG-43 formalism, (2) materials and nominal densities assigned to contours of foreign objects, (3) materials and nominal densities assigned to contoured organs in addition to foreign objects, and (4) materials specified as in (3) but with voxel mass densities derived from CT Hounsfield units. Clinical plans optimized for 192Ir were used, with the results for 75Se and 169Yb normalized to the D90 of the 192Ir clinical plan. RESULTS: In comparison to segmentation scheme 4, TG-43-based dosimetry overestimates CTV D90 by 6% (P = .00003), rectum D50 by 24% (P = .00003), and pelvic bone D50 by 5% (P = .00003) for 192Ir. For 169Yb, CTV D90 is overestimated by 17% (P = .00003) and rectum D50 by 39% (P = .00003), and pelvic bone D50 is significantly underestimated by 27% (P = .007). Postimplant dosimetry calculations also showed that a 169Yb source would give 20% (P = .00003) lower rectum V60 and 17% (P = .00008) lower rectum D50.
CONCLUSIONS: Ignoring high-Z materials in dose calculation contributes to inaccuracies that may lead to suboptimal dose optimization and disagreement between prescribed and calculated dose. This is especially important for low-energy radionuclides. Our results also show that with future magnetic resonance imaging-based treatment planning, loss of CT density data will only affect calculated dose in nonbone OARs by 2% or less and bone OARs by 13% or less across all sources if material composition and nominal mass densities are correctly assigned.2011
Xu, Chen; Verhaegen, Frank; Laurendeau, Denis; Enger, Shirin A.; Beaulieu, Luc
An algorithm for efficient metal artifact reductions in permanent seed Journal Article
In: Medical Physics, vol. 38, no. 1, pp. 47–56, 2011, ISSN: 0094-2405.
Abstract | Links | BibTeX | Tags: Algorithms, Artifacts, Brachytherapy, Humans, Imaging, Metals, Monte Carlo Method, Phantoms, Tomography, X-Ray Computed
@article{xu_algorithm_2011,
title = {An algorithm for efficient metal artifact reductions in permanent seed},
author = {Chen Xu and Frank Verhaegen and Denis Laurendeau and Shirin A. Enger and Luc Beaulieu},
doi = {10.1118/1.3519988},
issn = {0094-2405},
year = {2011},
date = {2011-01-01},
journal = {Medical Physics},
volume = {38},
number = {1},
pages = {47--56},
abstract = {PURPOSE: In permanent seed implants, 60 to more than 100 small metal capsules are inserted in the prostate, creating artifacts in x-ray computed tomography (CT) imaging. The goal of this work is to develop an automatic method for metal artifact reduction (MAR) from small objects such as brachytherapy seeds for clinical applications.
METHODS: The approach for MAR is based on the interpolation of missing projections by directly using raw helical CT data (sinogram). First, an initial image is reconstructed from the raw CT data. Then, the metal objects segmented from the reconstructed image are reprojected back into the sinogram space to produce a metal-only sinogram. The Steger method is used to determine precisely the position and edges of the seed traces in the raw CT data. By combining the use of Steger detection and reprojections, the missing projections are detected and replaced by interpolation of non-missing neighboring projections.
RESULTS: In both phantom experiments and patient studies, the missing projections have been detected successfully and the artifacts caused by metallic objects have been substantially reduced. The performance of the algorithm has been quantified by comparing the uniformity between the uncorrected and the corrected phantom images. The results of the artifact reduction algorithm are indistinguishable from the true background value.
CONCLUSIONS: An efficient algorithm for MAR in seed brachytherapy was developed. The test results obtained using raw helical CT data for both phantom and clinical cases have demonstrated that the proposed MAR method is capable of accurately detecting and correcting artifacts caused by a large number of very small metal objects (seeds) in sinogram space. This should enable a more accurate use of advanced brachytherapy dose calculations, such as Monte Carlo simulations.},
keywords = {Algorithms, Artifacts, Brachytherapy, Humans, Imaging, Metals, Monte Carlo Method, Phantoms, Tomography, X-Ray Computed},
pubstate = {published},
tppubtype = {article}
}
PURPOSE: In permanent seed implants, 60 to more than 100 small metal capsules are inserted in the prostate, creating artifacts in x-ray computed tomography (CT) imaging. The goal of this work is to develop an automatic method for metal artifact reduction (MAR) from small objects such as brachytherapy seeds for clinical applications.
METHODS: The approach for MAR is based on the interpolation of missing projections by directly using raw helical CT data (sinogram). First, an initial image is reconstructed from the raw CT data. Then, the metal objects segmented from the reconstructed image are reprojected back into the sinogram space to produce a metal-only sinogram. The Steger method is used to determine precisely the position and edges of the seed traces in the raw CT data. By combining the use of Steger detection and reprojections, the missing projections are detected and replaced by interpolation of non-missing neighboring projections.
RESULTS: In both phantom experiments and patient studies, the missing projections have been detected successfully and the artifacts caused by metallic objects have been substantially reduced. The performance of the algorithm has been quantified by comparing the uniformity between the uncorrected and the corrected phantom images. The results of the artifact reduction algorithm are indistinguishable from the true background value.
CONCLUSIONS: An efficient algorithm for MAR in seed brachytherapy was developed. The test results obtained using raw helical CT data for both phantom and clinical cases have demonstrated that the proposed MAR method is capable of accurately detecting and correcting artifacts caused by a large number of very small metal objects (seeds) in sinogram space. This should enable a more accurate use of advanced brachytherapy dose calculations, such as Monte Carlo simulations.
Journal Articles
2019
Shoemaker, Tristan; Vuong, Té; Glickman, Harry; Kaifi, Samar; Famulari, Gabriel; Enger, Shirin A.
Dosimetric Considerations for Ytterbium-169, Selenium-75, and Iridium-192 Radioisotopes in High-Dose-Rate Endorectal Brachytherapy Journal Article
In: International Journal of Radiation Oncology, Biology, Physics, vol. 105, no. 4, pp. 875–883, 2019, ISSN: 1879-355X.
Abstract | Links | BibTeX | Tags: Brachytherapy, Femur, Humans, Iridium Radioisotopes, Monte Carlo Method, Organs at Risk, Pelvic Bones, Radioisotopes, Radiotherapy Dosage, Rectal Neoplasms, Rectum, Selenium Radioisotopes, Tomography, Urinary Bladder, X-Ray Computed, Ytterbium
@article{shoemaker_dosimetric_2019,
title = {Dosimetric Considerations for Ytterbium-169, Selenium-75, and Iridium-192 Radioisotopes in High-Dose-Rate Endorectal Brachytherapy},
author = {Tristan Shoemaker and Té Vuong and Harry Glickman and Samar Kaifi and Gabriel Famulari and Shirin A. Enger},
doi = {10.1016/j.ijrobp.2019.07.003},
issn = {1879-355X},
year = {2019},
date = {2019-11-01},
journal = {International Journal of Radiation Oncology, Biology, Physics},
volume = {105},
number = {4},
pages = {875--883},
abstract = {PURPOSE: To investigate differences between prescribed and postimplant calculated dose in 192Ir high-dose-rate endorectal brachytherapy (HDR-EBT) by evaluating dose to clinical target volume (CTV) and organs at risk (OARs) calculated with a Monte Carlo-based dose calculation software, RapidBrachyMC. In addition, dose coverage, conformity, and homogeneity were compared among the radionuclides 192Ir, 75Se, and 169Yb for use in HDR-EBT.
METHODS AND MATERIALS: Postimplant dosimetry was evaluated using 23 computed tomography (CT) images from patients treated with HDR-EBT using the 192Ir microSelectron v2 (Elekta AB, Stockholm, Sweden) source and the Intracavitary Mold Applicator Set (Elekta AB, Stockholm, Sweden), which is a flexible applicator capable of fitting a tungsten rod for OAR shielding. Four tissue segmentation schemes were evaluated: (1) TG-43 formalism, (2) materials and nominal densities assigned to contours of foreign objects, (3) materials and nominal densities assigned to contoured organs in addition to foreign objects, and (4) materials specified as in (3) but with voxel mass densities derived from CT Hounsfield units. Clinical plans optimized for 192Ir were used, with the results for 75Se and 169Yb normalized to the D90 of the 192Ir clinical plan. RESULTS: In comparison to segmentation scheme 4, TG-43-based dosimetry overestimates CTV D90 by 6% (P = .00003), rectum D50 by 24% (P = .00003), and pelvic bone D50 by 5% (P = .00003) for 192Ir. For 169Yb, CTV D90 is overestimated by 17% (P = .00003) and rectum D50 by 39% (P = .00003), and pelvic bone D50 is significantly underestimated by 27% (P = .007). Postimplant dosimetry calculations also showed that a 169Yb source would give 20% (P = .00003) lower rectum V60 and 17% (P = .00008) lower rectum D50.
CONCLUSIONS: Ignoring high-Z materials in dose calculation contributes to inaccuracies that may lead to suboptimal dose optimization and disagreement between prescribed and calculated dose. This is especially important for low-energy radionuclides. Our results also show that with future magnetic resonance imaging-based treatment planning, loss of CT density data will only affect calculated dose in nonbone OARs by 2% or less and bone OARs by 13% or less across all sources if material composition and nominal mass densities are correctly assigned.},
keywords = {Brachytherapy, Femur, Humans, Iridium Radioisotopes, Monte Carlo Method, Organs at Risk, Pelvic Bones, Radioisotopes, Radiotherapy Dosage, Rectal Neoplasms, Rectum, Selenium Radioisotopes, Tomography, Urinary Bladder, X-Ray Computed, Ytterbium},
pubstate = {published},
tppubtype = {article}
}
PURPOSE: To investigate differences between prescribed and postimplant calculated dose in 192Ir high-dose-rate endorectal brachytherapy (HDR-EBT) by evaluating dose to clinical target volume (CTV) and organs at risk (OARs) calculated with a Monte Carlo-based dose calculation software, RapidBrachyMC. In addition, dose coverage, conformity, and homogeneity were compared among the radionuclides 192Ir, 75Se, and 169Yb for use in HDR-EBT.
METHODS AND MATERIALS: Postimplant dosimetry was evaluated using 23 computed tomography (CT) images from patients treated with HDR-EBT using the 192Ir microSelectron v2 (Elekta AB, Stockholm, Sweden) source and the Intracavitary Mold Applicator Set (Elekta AB, Stockholm, Sweden), which is a flexible applicator capable of fitting a tungsten rod for OAR shielding. Four tissue segmentation schemes were evaluated: (1) TG-43 formalism, (2) materials and nominal densities assigned to contours of foreign objects, (3) materials and nominal densities assigned to contoured organs in addition to foreign objects, and (4) materials specified as in (3) but with voxel mass densities derived from CT Hounsfield units. Clinical plans optimized for 192Ir were used, with the results for 75Se and 169Yb normalized to the D90 of the 192Ir clinical plan. RESULTS: In comparison to segmentation scheme 4, TG-43-based dosimetry overestimates CTV D90 by 6% (P = .00003), rectum D50 by 24% (P = .00003), and pelvic bone D50 by 5% (P = .00003) for 192Ir. For 169Yb, CTV D90 is overestimated by 17% (P = .00003) and rectum D50 by 39% (P = .00003), and pelvic bone D50 is significantly underestimated by 27% (P = .007). Postimplant dosimetry calculations also showed that a 169Yb source would give 20% (P = .00003) lower rectum V60 and 17% (P = .00008) lower rectum D50.
CONCLUSIONS: Ignoring high-Z materials in dose calculation contributes to inaccuracies that may lead to suboptimal dose optimization and disagreement between prescribed and calculated dose. This is especially important for low-energy radionuclides. Our results also show that with future magnetic resonance imaging-based treatment planning, loss of CT density data will only affect calculated dose in nonbone OARs by 2% or less and bone OARs by 13% or less across all sources if material composition and nominal mass densities are correctly assigned.
METHODS AND MATERIALS: Postimplant dosimetry was evaluated using 23 computed tomography (CT) images from patients treated with HDR-EBT using the 192Ir microSelectron v2 (Elekta AB, Stockholm, Sweden) source and the Intracavitary Mold Applicator Set (Elekta AB, Stockholm, Sweden), which is a flexible applicator capable of fitting a tungsten rod for OAR shielding. Four tissue segmentation schemes were evaluated: (1) TG-43 formalism, (2) materials and nominal densities assigned to contours of foreign objects, (3) materials and nominal densities assigned to contoured organs in addition to foreign objects, and (4) materials specified as in (3) but with voxel mass densities derived from CT Hounsfield units. Clinical plans optimized for 192Ir were used, with the results for 75Se and 169Yb normalized to the D90 of the 192Ir clinical plan. RESULTS: In comparison to segmentation scheme 4, TG-43-based dosimetry overestimates CTV D90 by 6% (P = .00003), rectum D50 by 24% (P = .00003), and pelvic bone D50 by 5% (P = .00003) for 192Ir. For 169Yb, CTV D90 is overestimated by 17% (P = .00003) and rectum D50 by 39% (P = .00003), and pelvic bone D50 is significantly underestimated by 27% (P = .007). Postimplant dosimetry calculations also showed that a 169Yb source would give 20% (P = .00003) lower rectum V60 and 17% (P = .00008) lower rectum D50.
CONCLUSIONS: Ignoring high-Z materials in dose calculation contributes to inaccuracies that may lead to suboptimal dose optimization and disagreement between prescribed and calculated dose. This is especially important for low-energy radionuclides. Our results also show that with future magnetic resonance imaging-based treatment planning, loss of CT density data will only affect calculated dose in nonbone OARs by 2% or less and bone OARs by 13% or less across all sources if material composition and nominal mass densities are correctly assigned.
2011
Xu, Chen; Verhaegen, Frank; Laurendeau, Denis; Enger, Shirin A.; Beaulieu, Luc
An algorithm for efficient metal artifact reductions in permanent seed Journal Article
In: Medical Physics, vol. 38, no. 1, pp. 47–56, 2011, ISSN: 0094-2405.
Abstract | Links | BibTeX | Tags: Algorithms, Artifacts, Brachytherapy, Humans, Imaging, Metals, Monte Carlo Method, Phantoms, Tomography, X-Ray Computed
@article{xu_algorithm_2011,
title = {An algorithm for efficient metal artifact reductions in permanent seed},
author = {Chen Xu and Frank Verhaegen and Denis Laurendeau and Shirin A. Enger and Luc Beaulieu},
doi = {10.1118/1.3519988},
issn = {0094-2405},
year = {2011},
date = {2011-01-01},
journal = {Medical Physics},
volume = {38},
number = {1},
pages = {47--56},
abstract = {PURPOSE: In permanent seed implants, 60 to more than 100 small metal capsules are inserted in the prostate, creating artifacts in x-ray computed tomography (CT) imaging. The goal of this work is to develop an automatic method for metal artifact reduction (MAR) from small objects such as brachytherapy seeds for clinical applications.
METHODS: The approach for MAR is based on the interpolation of missing projections by directly using raw helical CT data (sinogram). First, an initial image is reconstructed from the raw CT data. Then, the metal objects segmented from the reconstructed image are reprojected back into the sinogram space to produce a metal-only sinogram. The Steger method is used to determine precisely the position and edges of the seed traces in the raw CT data. By combining the use of Steger detection and reprojections, the missing projections are detected and replaced by interpolation of non-missing neighboring projections.
RESULTS: In both phantom experiments and patient studies, the missing projections have been detected successfully and the artifacts caused by metallic objects have been substantially reduced. The performance of the algorithm has been quantified by comparing the uniformity between the uncorrected and the corrected phantom images. The results of the artifact reduction algorithm are indistinguishable from the true background value.
CONCLUSIONS: An efficient algorithm for MAR in seed brachytherapy was developed. The test results obtained using raw helical CT data for both phantom and clinical cases have demonstrated that the proposed MAR method is capable of accurately detecting and correcting artifacts caused by a large number of very small metal objects (seeds) in sinogram space. This should enable a more accurate use of advanced brachytherapy dose calculations, such as Monte Carlo simulations.},
keywords = {Algorithms, Artifacts, Brachytherapy, Humans, Imaging, Metals, Monte Carlo Method, Phantoms, Tomography, X-Ray Computed},
pubstate = {published},
tppubtype = {article}
}
PURPOSE: In permanent seed implants, 60 to more than 100 small metal capsules are inserted in the prostate, creating artifacts in x-ray computed tomography (CT) imaging. The goal of this work is to develop an automatic method for metal artifact reduction (MAR) from small objects such as brachytherapy seeds for clinical applications.
METHODS: The approach for MAR is based on the interpolation of missing projections by directly using raw helical CT data (sinogram). First, an initial image is reconstructed from the raw CT data. Then, the metal objects segmented from the reconstructed image are reprojected back into the sinogram space to produce a metal-only sinogram. The Steger method is used to determine precisely the position and edges of the seed traces in the raw CT data. By combining the use of Steger detection and reprojections, the missing projections are detected and replaced by interpolation of non-missing neighboring projections.
RESULTS: In both phantom experiments and patient studies, the missing projections have been detected successfully and the artifacts caused by metallic objects have been substantially reduced. The performance of the algorithm has been quantified by comparing the uniformity between the uncorrected and the corrected phantom images. The results of the artifact reduction algorithm are indistinguishable from the true background value.
CONCLUSIONS: An efficient algorithm for MAR in seed brachytherapy was developed. The test results obtained using raw helical CT data for both phantom and clinical cases have demonstrated that the proposed MAR method is capable of accurately detecting and correcting artifacts caused by a large number of very small metal objects (seeds) in sinogram space. This should enable a more accurate use of advanced brachytherapy dose calculations, such as Monte Carlo simulations.
METHODS: The approach for MAR is based on the interpolation of missing projections by directly using raw helical CT data (sinogram). First, an initial image is reconstructed from the raw CT data. Then, the metal objects segmented from the reconstructed image are reprojected back into the sinogram space to produce a metal-only sinogram. The Steger method is used to determine precisely the position and edges of the seed traces in the raw CT data. By combining the use of Steger detection and reprojections, the missing projections are detected and replaced by interpolation of non-missing neighboring projections.
RESULTS: In both phantom experiments and patient studies, the missing projections have been detected successfully and the artifacts caused by metallic objects have been substantially reduced. The performance of the algorithm has been quantified by comparing the uniformity between the uncorrected and the corrected phantom images. The results of the artifact reduction algorithm are indistinguishable from the true background value.
CONCLUSIONS: An efficient algorithm for MAR in seed brachytherapy was developed. The test results obtained using raw helical CT data for both phantom and clinical cases have demonstrated that the proposed MAR method is capable of accurately detecting and correcting artifacts caused by a large number of very small metal objects (seeds) in sinogram space. This should enable a more accurate use of advanced brachytherapy dose calculations, such as Monte Carlo simulations.