Journal Articles
2021
Development of patient-specific 3D models from histopathological samples for applications in radiation therapy Journal Article
In: Physica medica: PM: an international journal devoted to the applications of physics to medicine and biology: official journal of the Italian Association of Biomedical Physics (AIFB), vol. 81, pp. 162–169, 2021, ISSN: 1724-191X.
@article{decunha_development_2021,
title = {Development of patient-specific 3D models from histopathological samples for applications in radiation therapy},
author = {Joseph M. DeCunha and Christopher M. Poole and Martin Vallières and Jose Torres and Sophie Camilleri-Broët and Roni F. Rayes and Jonathan D. Spicer and Shirin A. Enger},
doi = {10.1016/j.ejmp.2020.12.009},
issn = {1724-191X},
year = {2021},
date = {2021-01-01},
journal = {Physica medica: PM: an international journal devoted to the applications of physics to medicine and biology: official journal of the Italian Association of Biomedical Physics (AIFB)},
volume = {81},
pages = {162--169},
abstract = {The biological effects of ionizing radiation depend on the tissue, tumor type, radiation quality, and patient-specific factors. Inter-patient variation in cell/nucleus size may influence patient-specific dose response. However, this variability in dose response is not well investigated due to lack of available cell/nucleus size data. The aim of this study was to develop methods to derive cell/nucleus size distributions from digital images of 2D histopathological samples and use them to build digital 3D models for use in cellular dosimetry. Nineteen of sixty hematoxylin and eosin stained lung adenocarcinoma samples investigated passed exclusion criterion to be analyzed in the study. A difference of gaussians blob detection algorithm was used to identify nucleus centers and quantify cell spacing. Hematoxylin content was measured to determine nucleus radius. Pouring simulations were conducted to generate one-hundred 3D models containing volumes of equivalent cell spacing and nuclei radius to those in histopathological samples. The nuclei radius distributions of non-tumoral and cancerous regions appearing in the same slide were significantly different (p textless 0.01) in all samples analyzed. The median nuclear-cytoplasmic ratio was 0.36 for non-tumoral cells and 0.50 for cancerous cells. The average cellular and nucleus packing densities in the 3D models generated were 65.9% (SD: 1.5%) and 13.3% (SD: 0.3%) respectively. Software to determine cell spacing and nuclei radius from histopathological samples was developed. 3D digital tissue models containing volumes with equivalent cell spacing, nucleus radius, and packing density to cancerous tissues were generated.},
keywords = {Algorithms, Cell Nucleus, Cellular dosimetry, Histopathology, Humans, Microdosimetry, Patient-specific, Radiometry},
pubstate = {published},
tppubtype = {article}
}
The biological effects of ionizing radiation depend on the tissue, tumor type, radiation quality, and patient-specific factors. Inter-patient variation in cell/nucleus size may influence patient-specific dose response. However, this variability in dose response is not well investigated due to lack of available cell/nucleus size data. The aim of this study was to develop methods to derive cell/nucleus size distributions from digital images of 2D histopathological samples and use them to build digital 3D models for use in cellular dosimetry. Nineteen of sixty hematoxylin and eosin stained lung adenocarcinoma samples investigated passed exclusion criterion to be analyzed in the study. A difference of gaussians blob detection algorithm was used to identify nucleus centers and quantify cell spacing. Hematoxylin content was measured to determine nucleus radius. Pouring simulations were conducted to generate one-hundred 3D models containing volumes of equivalent cell spacing and nuclei radius to those in histopathological samples. The nuclei radius distributions of non-tumoral and cancerous regions appearing in the same slide were significantly different (p textless 0.01) in all samples analyzed. The median nuclear-cytoplasmic ratio was 0.36 for non-tumoral cells and 0.50 for cancerous cells. The average cellular and nucleus packing densities in the 3D models generated were 65.9% (SD: 1.5%) and 13.3% (SD: 0.3%) respectively. Software to determine cell spacing and nuclei radius from histopathological samples was developed. 3D digital tissue models containing volumes with equivalent cell spacing, nucleus radius, and packing density to cancerous tissues were generated.2020
Fast mixed integer optimization (FMIO) for high dose rate brachytherapy Journal Article
In: Physics in Medicine and Biology, vol. 65, no. 21, pp. 215005, 2020, ISSN: 1361-6560.
@article{antaki_fast_2020,
title = {Fast mixed integer optimization (FMIO) for high dose rate brachytherapy},
author = {Majd Antaki and Christopher L Deufel and Shirin A. Enger},
doi = {10.1088/1361-6560/aba317},
issn = {1361-6560},
year = {2020},
date = {2020-12-01},
journal = {Physics in Medicine and Biology},
volume = {65},
number = {21},
pages = {215005},
abstract = {The purpose of this work was to develop an efficient quadratic mixed integer programming algorithm for high dose rate (HDR) brachytherapy treatment planning problems and integrate the algorithm into an open-source Monte Carlo based treatment planning software, RapidBrachyMCTPS. The mixed-integer algorithm yields a globally optimum solution to the dose volume histogram (DVH) based problem and, unlike other methods, is not susceptible to local minimum trapping. A hybrid linear-quadratic penalty model coupled to a mixed integer programming model was used to optimize treatment plans for 10 prostate cancer patients. Dose distributions for each dwell position were calculated with RapidBrachyMCTPS with type A uncertainties less than 0.2% in voxels within the planning target volume (PTV). The optimization process was divided into two parts. First, the data was preprocessed, in which the problem size was reduced by eliminating voxels that had negligible impact on the solution (e.g. far from the dwell position). Second, the best combination of dwell times to obtain a plan with the highest score was found. The dwell positions and dose volume constraints were used as input to a commercial mixed integer optimizer (Gurobi Optimization, Inc.). A penalty-based criterion was adopted for the scoring. The voxel-reduction technique successfully reduced the problem size by an average of 91%, without loss of quality. The preprocessing of the optimization process required on average 4 s and solving for the global maximum required on average 33 s. The total optimization time averaged 37 s, which is a substantial improvement over the ∼15 min optimization time reported in published literature. The plan quality was evaluated by evaluating dose volume metrics, including PTV D90, rectum and bladder D1cc and urethra D0.1cc. In conclusion, fast mixed integer optimization is an order of magnitude faster than current mixed-integer approaches for solving HDR brachytherapy treatment planning problems with DVH based metrics.},
keywords = {Algorithms, Brachytherapy, Computer-Assisted, Humans, Linear Models, Male, Monte Carlo Method, Prostatic Neoplasms, Radiation Dosage, Radiotherapy Dosage, Radiotherapy Planning, Software, Time Factors},
pubstate = {published},
tppubtype = {article}
}
The purpose of this work was to develop an efficient quadratic mixed integer programming algorithm for high dose rate (HDR) brachytherapy treatment planning problems and integrate the algorithm into an open-source Monte Carlo based treatment planning software, RapidBrachyMCTPS. The mixed-integer algorithm yields a globally optimum solution to the dose volume histogram (DVH) based problem and, unlike other methods, is not susceptible to local minimum trapping. A hybrid linear-quadratic penalty model coupled to a mixed integer programming model was used to optimize treatment plans for 10 prostate cancer patients. Dose distributions for each dwell position were calculated with RapidBrachyMCTPS with type A uncertainties less than 0.2% in voxels within the planning target volume (PTV). The optimization process was divided into two parts. First, the data was preprocessed, in which the problem size was reduced by eliminating voxels that had negligible impact on the solution (e.g. far from the dwell position). Second, the best combination of dwell times to obtain a plan with the highest score was found. The dwell positions and dose volume constraints were used as input to a commercial mixed integer optimizer (Gurobi Optimization, Inc.). A penalty-based criterion was adopted for the scoring. The voxel-reduction technique successfully reduced the problem size by an average of 91%, without loss of quality. The preprocessing of the optimization process required on average 4 s and solving for the global maximum required on average 33 s. The total optimization time averaged 37 s, which is a substantial improvement over the ∼15 min optimization time reported in published literature. The plan quality was evaluated by evaluating dose volume metrics, including PTV D90, rectum and bladder D1cc and urethra D0.1cc. In conclusion, fast mixed integer optimization is an order of magnitude faster than current mixed-integer approaches for solving HDR brachytherapy treatment planning problems with DVH based metrics.In: Physica medica: PM: an international journal devoted to the applications of physics to medicine and biology: official journal of the Italian Association of Biomedical Physics (AIFB), vol. 76, pp. 92–99, 2020, ISSN: 1724-191X.
@article{carroll_cross-validation_2020,
title = {Cross-validation of a non-invasive positron detector to measure the arterial input function for pharmacokinetic modelling in dynamic positron emission tomography},
author = {Liam Carroll and Etienne Croteau and Gustavo Kertzscher and Otman Sarrhini and Vincent Turgeon and Roger Lecomte and Shirin A. Enger},
doi = {10.1016/j.ejmp.2020.06.009},
issn = {1724-191X},
year = {2020},
date = {2020-08-01},
journal = {Physica medica: PM: an international journal devoted to the applications of physics to medicine and biology: official journal of the Italian Association of Biomedical Physics (AIFB)},
volume = {76},
pages = {92--99},
abstract = {Kinetic modeling of positron emission tomography (PET) data can assess index rate of uptake, metabolism and predict disease progression more accurately than conventional static PET. However, it requires knowledge of the time-course of the arterial blood radioactivity concentration, called the arterial input function (AIF). The gold standard to acquire the AIF is by invasive means. The purpose of this study was to validate a previously developed dual readout scintillating fiber-based non-invasive positron detector, hereinafter called non-invasive detector (NID), developed to determine the AIF for dynamic PET measured from the human radial artery. The NID consisted of a 3 m long plastic scintillating fiber with each end coupled to a 5 m long transmission fiber followed by a silicon photomultiplier. The scintillating fiber was enclosed inside the grooves of a plastic cylindrical shell. Two sets of experiments were performed to test the NID against a previously validated microfluidic positron detector. A closed-loop microfluidic system combined with a wrist phantom was used. During the first experiment, the three PET radioisotopes 18F, 11C and 68Ga were tested. After optimizing the detector, a second series of tests were performed using only 18F and 11C. The maximum pulse amplitude to electronic noise ratio was 52 obtained with 11C. Linear regressions showed a linear relation between the two detectors. These preliminary results show that the NID can accurately detect positrons from a patient's wrist and has the potential to non-invasively measure the AIF during a dynamic PET scan. The accuracy of these measurements needs to be determined.},
keywords = {Algorithms, Arterial input function, Arteries, Dynamic PET, Electrons, Humans, Imaging, Non-invasive detector development, Phantoms, Positron-Emission Tomography, Scintillation},
pubstate = {published},
tppubtype = {article}
}
Kinetic modeling of positron emission tomography (PET) data can assess index rate of uptake, metabolism and predict disease progression more accurately than conventional static PET. However, it requires knowledge of the time-course of the arterial blood radioactivity concentration, called the arterial input function (AIF). The gold standard to acquire the AIF is by invasive means. The purpose of this study was to validate a previously developed dual readout scintillating fiber-based non-invasive positron detector, hereinafter called non-invasive detector (NID), developed to determine the AIF for dynamic PET measured from the human radial artery. The NID consisted of a 3 m long plastic scintillating fiber with each end coupled to a 5 m long transmission fiber followed by a silicon photomultiplier. The scintillating fiber was enclosed inside the grooves of a plastic cylindrical shell. Two sets of experiments were performed to test the NID against a previously validated microfluidic positron detector. A closed-loop microfluidic system combined with a wrist phantom was used. During the first experiment, the three PET radioisotopes 18F, 11C and 68Ga were tested. After optimizing the detector, a second series of tests were performed using only 18F and 11C. The maximum pulse amplitude to electronic noise ratio was 52 obtained with 11C. Linear regressions showed a linear relation between the two detectors. These preliminary results show that the NID can accurately detect positrons from a patient’s wrist and has the potential to non-invasively measure the AIF during a dynamic PET scan. The accuracy of these measurements needs to be determined.Model-Based Dose Calculation Algorithms for Brachytherapy Dosimetry Journal Article
In: Seminars in Radiation Oncology, vol. 30, no. 1, pp. 77–86, 2020, ISSN: 1532-9461.
@article{enger_model-based_2020,
title = {Model-Based Dose Calculation Algorithms for Brachytherapy Dosimetry},
author = {Shirin A. Enger and Javier Vijande and Mark J. Rivard},
doi = {10.1016/j.semradonc.2019.08.006},
issn = {1532-9461},
year = {2020},
date = {2020-01-01},
journal = {Seminars in Radiation Oncology},
volume = {30},
number = {1},
pages = {77--86},
abstract = {The purpose of this study was to review the limitations of dose calculation formalisms for photon-emitting brachytherapy sources based on the American Association of Physicists in Medicine (AAPM) Task Group No. 43 (TG-43) report and to provide recommendations to transition to model-based dose calculation algorithms. Additionally, an overview of these algorithms and approaches is presented. The influence of tissue and seed/applicator heterogeneities on brachytherapy dose distributions for breast, gynecologic, head and neck, rectum, and prostate cancers as well as eye plaques and electronic brachytherapy treatments were investigated by comparing dose calculations based on the TG-43 formalism and model-based dose calculation algorithms.},
keywords = {Algorithms, Brachytherapy, Computer-Assisted, Female, Humans, Male, Medical, Models, Neoplasms, Photons, Practice Guidelines as Topic, Radiometry, Radiotherapy Dosage, Radiotherapy Planning, Societies, Theoretical},
pubstate = {published},
tppubtype = {article}
}
The purpose of this study was to review the limitations of dose calculation formalisms for photon-emitting brachytherapy sources based on the American Association of Physicists in Medicine (AAPM) Task Group No. 43 (TG-43) report and to provide recommendations to transition to model-based dose calculation algorithms. Additionally, an overview of these algorithms and approaches is presented. The influence of tissue and seed/applicator heterogeneities on brachytherapy dose distributions for breast, gynecologic, head and neck, rectum, and prostate cancers as well as eye plaques and electronic brachytherapy treatments were investigated by comparing dose calculations based on the TG-43 formalism and model-based dose calculation algorithms.2018
The influence of tissue composition uncertainty on dose distributions in brachytherapy Journal Article
In: Radiotherapy and Oncology: Journal of the European Society for Therapeutic Radiology and Oncology, vol. 126, no. 3, pp. 394–410, 2018, ISSN: 1879-0887.
@article{mann-krzisnik_influence_2018,
title = {The influence of tissue composition uncertainty on dose distributions in brachytherapy},
author = {Dylan Mann-Krzisnik and Frank Verhaegen and Shirin A. Enger},
doi = {10.1016/j.radonc.2018.01.007},
issn = {1879-0887},
year = {2018},
date = {2018-03-01},
journal = {Radiotherapy and Oncology: Journal of the European Society for Therapeutic Radiology and Oncology},
volume = {126},
number = {3},
pages = {394--410},
abstract = {BACKGROUND AND PURPOSE: Model-based dose calculation algorithms (MBDCAs) have evolved from serving as a research tool into clinical practice in brachytherapy. This study investigates primary sources of tissue elemental compositions used as input to MBDCAs and the impact of their variability on MBDCA-based dosimetry.
MATERIALS AND METHODS: Relevant studies were retrieved through PubMed. Minimum dose delivered to 90% of the target (D90), minimum dose delivered to the hottest specified volume for organs at risk (OAR) and mass energy-absorption coefficients (μen/ρ) generated by using EGSnrc "g" user-code were compared to assess the impact of compositional variability.
RESULTS: Elemental composition for hydrogen, carbon, oxygen and nitrogen are derived from the gross contents of fats, proteins and carbohydrates for any given tissue, the compositions of which are taken from literature dating back to 1940-1950. Heavier elements are derived from studies performed in the 1950-1960. Variability in elemental composition impacts greatly D90 for target tissues and doses to OAR for brachytherapy with low energy sources and less for 192Ir-based brachytherapy. Discrepancies in μen/ρ are also indicative of dose differences.
CONCLUSIONS: Updated elemental compositions are needed to optimize MBDCA-based dosimetry. Until then, tissue compositions based on gross simplifications in early studies will dominate the uncertainties in tissue heterogeneity.},
keywords = {Algorithms, Body Composition, Brachytherapy, Elemental composition, Humans, Mass energy-absorption coefficient, MBDCA, Organs at Risk, Radiotherapy Dosage, Review, Tissue heterogeneity, Uncertainty},
pubstate = {published},
tppubtype = {article}
}
BACKGROUND AND PURPOSE: Model-based dose calculation algorithms (MBDCAs) have evolved from serving as a research tool into clinical practice in brachytherapy. This study investigates primary sources of tissue elemental compositions used as input to MBDCAs and the impact of their variability on MBDCA-based dosimetry.
MATERIALS AND METHODS: Relevant studies were retrieved through PubMed. Minimum dose delivered to 90% of the target (D90), minimum dose delivered to the hottest specified volume for organs at risk (OAR) and mass energy-absorption coefficients (μen/ρ) generated by using EGSnrc “g” user-code were compared to assess the impact of compositional variability.
RESULTS: Elemental composition for hydrogen, carbon, oxygen and nitrogen are derived from the gross contents of fats, proteins and carbohydrates for any given tissue, the compositions of which are taken from literature dating back to 1940-1950. Heavier elements are derived from studies performed in the 1950-1960. Variability in elemental composition impacts greatly D90 for target tissues and doses to OAR for brachytherapy with low energy sources and less for 192Ir-based brachytherapy. Discrepancies in μen/ρ are also indicative of dose differences.
CONCLUSIONS: Updated elemental compositions are needed to optimize MBDCA-based dosimetry. Until then, tissue compositions based on gross simplifications in early studies will dominate the uncertainties in tissue heterogeneity.2017
Microdosimetry calculations for monoenergetic electrons using Geant4-DNA combined with a weighted track sampling algorithm Journal Article
In: Physics in Medicine and Biology, vol. 62, no. 13, pp. 5495–5508, 2017, ISSN: 1361-6560.
@article{famulari_microdosimetry_2017,
title = {Microdosimetry calculations for monoenergetic electrons using Geant4-DNA combined with a weighted track sampling algorithm},
author = {Gabriel Famulari and Piotr Pater and Shirin A. Enger},
doi = {10.1088/1361-6560/aa71f6},
issn = {1361-6560},
year = {2017},
date = {2017-07-01},
journal = {Physics in Medicine and Biology},
volume = {62},
number = {13},
pages = {5495--5508},
abstract = {The aim of this study was to calculate microdosimetric distributions for low energy electrons simulated using the Monte Carlo track structure code Geant4-DNA. Tracks for monoenergetic electrons with kinetic energies ranging from 100 eV to 1 MeV were simulated in an infinite spherical water phantom using the Geant4-DNA extension included in Geant4 toolkit version 10.2 (patch 02). The microdosimetric distributions were obtained through random sampling of transfer points and overlaying scoring volumes within the associated volume of the tracks. Relative frequency distributions of energy deposition f(textgreaterE)/f(textgreater0) and dose mean lineal energy ([Formula: see text]) values were calculated in nanometer-sized spherical and cylindrical targets. The effects of scoring volume and scoring techniques were examined. The results were compared with published data generated using MOCA8B and KURBUC. Geant4-DNA produces a lower frequency of higher energy deposits than MOCA8B. The [Formula: see text] values calculated with Geant4-DNA are smaller than those calculated using MOCA8B and KURBUC. The differences are mainly due to the lower ionization and excitation cross sections of Geant4-DNA for low energy electrons. To a lesser extent, discrepancies can also be attributed to the implementation in this study of a new and fast scoring technique that differs from that used in previous studies. For the same mean chord length ([Formula: see text]), the [Formula: see text] calculated in cylindrical volumes are larger than those calculated in spherical volumes. The discrepancies due to cross sections and scoring geometries increase with decreasing scoring site dimensions. A new set of [Formula: see text] values has been presented for monoenergetic electrons using a fast track sampling algorithm and the most recent physics models implemented in Geant4-DNA. This dataset can be combined with primary electron spectra to predict the radiation quality of photon and electron beams.},
keywords = {Algorithms, DNA, DNA Damage, Electrons, Imaging, Monte Carlo Method, Phantoms, Photons, Radiometry},
pubstate = {published},
tppubtype = {article}
}
The aim of this study was to calculate microdosimetric distributions for low energy electrons simulated using the Monte Carlo track structure code Geant4-DNA. Tracks for monoenergetic electrons with kinetic energies ranging from 100 eV to 1 MeV were simulated in an infinite spherical water phantom using the Geant4-DNA extension included in Geant4 toolkit version 10.2 (patch 02). The microdosimetric distributions were obtained through random sampling of transfer points and overlaying scoring volumes within the associated volume of the tracks. Relative frequency distributions of energy deposition f(textgreaterE)/f(textgreater0) and dose mean lineal energy ([Formula: see text]) values were calculated in nanometer-sized spherical and cylindrical targets. The effects of scoring volume and scoring techniques were examined. The results were compared with published data generated using MOCA8B and KURBUC. Geant4-DNA produces a lower frequency of higher energy deposits than MOCA8B. The [Formula: see text] values calculated with Geant4-DNA are smaller than those calculated using MOCA8B and KURBUC. The differences are mainly due to the lower ionization and excitation cross sections of Geant4-DNA for low energy electrons. To a lesser extent, discrepancies can also be attributed to the implementation in this study of a new and fast scoring technique that differs from that used in previous studies. For the same mean chord length ([Formula: see text]), the [Formula: see text] calculated in cylindrical volumes are larger than those calculated in spherical volumes. The discrepancies due to cross sections and scoring geometries increase with decreasing scoring site dimensions. A new set of [Formula: see text] values has been presented for monoenergetic electrons using a fast track sampling algorithm and the most recent physics models implemented in Geant4-DNA. This dataset can be combined with primary electron spectra to predict the radiation quality of photon and electron beams.2015
Determination of subcellular compartment sizes for estimating dose variations in radiotherapy Journal Article
In: Radiation Protection Dosimetry, vol. 166, no. 1-4, pp. 361–364, 2015, ISSN: 1742-3406.
@article{poole_determination_2015,
title = {Determination of subcellular compartment sizes for estimating dose variations in radiotherapy},
author = {Christopher M. Poole and Anders Ahnesjö and Shirin A. Enger},
doi = {10.1093/rpd/ncv305},
issn = {1742-3406},
year = {2015},
date = {2015-09-01},
journal = {Radiation Protection Dosimetry},
volume = {166},
number = {1-4},
pages = {361--364},
abstract = {The variation in specific energy absorbed to different cell compartments caused by variations in size and chemical composition is poorly investigated in radiotherapy. The aim of this study was to develop an algorithm to derive cell and cell nuclei size distributions from 2D histology samples, and build 3D cellular geometries to provide Monte Carlo (MC)-based dose calculation engines with a morphologically relevant input geometry. Stained and unstained regions of the histology samples are segmented using a Gaussian mixture model, and individual cell nuclei are identified via thresholding. Delaunay triangulation is applied to determine the distribution of distances between the centroids of nearest neighbour cells. A pouring simulation is used to build a 3D virtual tissue sample, with cell radii randomised according to the cell size distribution determined from the histology samples. A slice with the same thickness as the histology sample is cut through the 3D data and characterised in the same way as the measured histology. The comparison between this virtual slice and the measured histology is used to adjust the initial cell size distribution into the pouring simulation. This iterative approach of a pouring simulation with adjustments guided by comparison is continued until an input cell size distribution is found that yields a distribution in the sliced geometry that agrees with the measured histology samples. The thus obtained morphologically realistic 3D cellular geometry can be used as input to MC-based dose calculation programs for studies of dose response due to variations in morphology and size of tumour/healthy tissue cells/nuclei, and extracellular material.},
keywords = {Algorithms, Breast Neoplasms, Cell Nucleus, Computer Simulation, Computer-Assisted, ErbB-2, Female, Humans, Image Processing, Imaging, Immunoenzyme Techniques, Male, Monte Carlo Method, Prostatic Neoplasms, Radiotherapy Dosage, Radiotherapy Planning, Receptor, Signal Processing, Subcellular Fractions, Three-Dimensional},
pubstate = {published},
tppubtype = {article}
}
The variation in specific energy absorbed to different cell compartments caused by variations in size and chemical composition is poorly investigated in radiotherapy. The aim of this study was to develop an algorithm to derive cell and cell nuclei size distributions from 2D histology samples, and build 3D cellular geometries to provide Monte Carlo (MC)-based dose calculation engines with a morphologically relevant input geometry. Stained and unstained regions of the histology samples are segmented using a Gaussian mixture model, and individual cell nuclei are identified via thresholding. Delaunay triangulation is applied to determine the distribution of distances between the centroids of nearest neighbour cells. A pouring simulation is used to build a 3D virtual tissue sample, with cell radii randomised according to the cell size distribution determined from the histology samples. A slice with the same thickness as the histology sample is cut through the 3D data and characterised in the same way as the measured histology. The comparison between this virtual slice and the measured histology is used to adjust the initial cell size distribution into the pouring simulation. This iterative approach of a pouring simulation with adjustments guided by comparison is continued until an input cell size distribution is found that yields a distribution in the sliced geometry that agrees with the measured histology samples. The thus obtained morphologically realistic 3D cellular geometry can be used as input to MC-based dose calculation programs for studies of dose response due to variations in morphology and size of tumour/healthy tissue cells/nuclei, and extracellular material.2011
Modeling a hypothetical 170Tm source for brachytherapy applications Journal Article
In: Medical Physics, vol. 38, no. 10, pp. 5307–5310, 2011, ISSN: 0094-2405.
@article{enger_modeling_2011,
title = {Modeling a hypothetical 170Tm source for brachytherapy applications},
author = {Shirin A. Enger and Michel D'Amours and Luc Beaulieu},
doi = {10.1118/1.3626482},
issn = {0094-2405},
year = {2011},
date = {2011-10-01},
journal = {Medical Physics},
volume = {38},
number = {10},
pages = {5307--5310},
abstract = {PURPOSE: To perform absorbed dose calculations based on Monte Carlo simulations for a hypothetical (170)Tm source and to investigate the influence of encapsulating material on the energy spectrum of the emitted electrons and photons.
METHODS: GEANT4 Monte Carlo code version 9.2 patch 2 was used to simulate the decay process of (170)Tm and to calculate the absorbed dose distribution using the GEANT4 Penelope physics models. A hypothetical (170)Tm source based on the Flexisource brachytherapy design with the active core set as a pure thulium cylinder (length 3.5 mm and diameter 0.6 mm) and different cylindrical source encapsulations (length 5 mm and thickness 0.125 mm) constructed of titanium, stainless-steel, gold, or platinum were simulated. The radial dose function for the line source approximation was calculated following the TG-43U1 formalism for the stainless-steel encapsulation.
RESULTS: For the titanium and stainless-steel encapsulation, 94% of the total bremsstrahlung is produced inside the core, 4.8 and 5.5% in titanium and stainless-steel capsules, respectively, and less than 1% in water. For the gold capsule, 85% is produced inside the core, 14.2% inside the gold capsule, and a negligible amount (textless1%) in water. Platinum encapsulation resulted in bremsstrahlung effects similar to those with the gold encapsulation. The range of the beta particles decreases by 1.1 mm with the stainless-steel encapsulation compared to the bare source but the tissue will still receive dose from the beta particles several millimeters from the source capsule. The gold and platinum capsules not only absorb most of the electrons but also attenuate low energy photons. The mean energy of the photons escaping the core and the stainless-steel capsule is 113 keV while for the gold and platinum the mean energy is 160 keV and 165 keV, respectively.
CONCLUSIONS: A (170)Tm source is primarily a bremsstrahlung source, with the majority of bremsstrahlung photons being generated in the source core and experiencing little attenuation in the source encapsulation. Electrons are efficiently absorbed by the gold and platinum encapsulations. However, for the stainless-steel capsule (or other lower Z encapsulations) electrons will escape. The dose from these electrons is dominant over the photon dose in the first few millimeter but is not taken into account by current standard treatment planning systems. The total energy spectrum of photons emerging from the source depends on the encapsulation composition and results in mean photon energies well above 100 keV. This is higher than the main gamma-ray energy peak at 84 keV. Based on our results, the use of (170)Tm as a brachytherapy source presents notable challenges.},
keywords = {Algorithms, Brachytherapy, Computer Simulation, Computer-Assisted, Electrons, Equipment Design, Gold, Humans, Models, Monte Carlo Method, Photons, Platinum, Radioisotopes, Radiotherapy Planning, Stainless Steel, Theoretical, Thulium, Titanium},
pubstate = {published},
tppubtype = {article}
}
PURPOSE: To perform absorbed dose calculations based on Monte Carlo simulations for a hypothetical (170)Tm source and to investigate the influence of encapsulating material on the energy spectrum of the emitted electrons and photons.
METHODS: GEANT4 Monte Carlo code version 9.2 patch 2 was used to simulate the decay process of (170)Tm and to calculate the absorbed dose distribution using the GEANT4 Penelope physics models. A hypothetical (170)Tm source based on the Flexisource brachytherapy design with the active core set as a pure thulium cylinder (length 3.5 mm and diameter 0.6 mm) and different cylindrical source encapsulations (length 5 mm and thickness 0.125 mm) constructed of titanium, stainless-steel, gold, or platinum were simulated. The radial dose function for the line source approximation was calculated following the TG-43U1 formalism for the stainless-steel encapsulation.
RESULTS: For the titanium and stainless-steel encapsulation, 94% of the total bremsstrahlung is produced inside the core, 4.8 and 5.5% in titanium and stainless-steel capsules, respectively, and less than 1% in water. For the gold capsule, 85% is produced inside the core, 14.2% inside the gold capsule, and a negligible amount (textless1%) in water. Platinum encapsulation resulted in bremsstrahlung effects similar to those with the gold encapsulation. The range of the beta particles decreases by 1.1 mm with the stainless-steel encapsulation compared to the bare source but the tissue will still receive dose from the beta particles several millimeters from the source capsule. The gold and platinum capsules not only absorb most of the electrons but also attenuate low energy photons. The mean energy of the photons escaping the core and the stainless-steel capsule is 113 keV while for the gold and platinum the mean energy is 160 keV and 165 keV, respectively.
CONCLUSIONS: A (170)Tm source is primarily a bremsstrahlung source, with the majority of bremsstrahlung photons being generated in the source core and experiencing little attenuation in the source encapsulation. Electrons are efficiently absorbed by the gold and platinum encapsulations. However, for the stainless-steel capsule (or other lower Z encapsulations) electrons will escape. The dose from these electrons is dominant over the photon dose in the first few millimeter but is not taken into account by current standard treatment planning systems. The total energy spectrum of photons emerging from the source depends on the encapsulation composition and results in mean photon energies well above 100 keV. This is higher than the main gamma-ray energy peak at 84 keV. Based on our results, the use of (170)Tm as a brachytherapy source presents notable challenges.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.
@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
2021
Development of patient-specific 3D models from histopathological samples for applications in radiation therapy Journal Article
In: Physica medica: PM: an international journal devoted to the applications of physics to medicine and biology: official journal of the Italian Association of Biomedical Physics (AIFB), vol. 81, pp. 162–169, 2021, ISSN: 1724-191X.
@article{decunha_development_2021,
title = {Development of patient-specific 3D models from histopathological samples for applications in radiation therapy},
author = {Joseph M. DeCunha and Christopher M. Poole and Martin Vallières and Jose Torres and Sophie Camilleri-Broët and Roni F. Rayes and Jonathan D. Spicer and Shirin A. Enger},
doi = {10.1016/j.ejmp.2020.12.009},
issn = {1724-191X},
year = {2021},
date = {2021-01-01},
journal = {Physica medica: PM: an international journal devoted to the applications of physics to medicine and biology: official journal of the Italian Association of Biomedical Physics (AIFB)},
volume = {81},
pages = {162--169},
abstract = {The biological effects of ionizing radiation depend on the tissue, tumor type, radiation quality, and patient-specific factors. Inter-patient variation in cell/nucleus size may influence patient-specific dose response. However, this variability in dose response is not well investigated due to lack of available cell/nucleus size data. The aim of this study was to develop methods to derive cell/nucleus size distributions from digital images of 2D histopathological samples and use them to build digital 3D models for use in cellular dosimetry. Nineteen of sixty hematoxylin and eosin stained lung adenocarcinoma samples investigated passed exclusion criterion to be analyzed in the study. A difference of gaussians blob detection algorithm was used to identify nucleus centers and quantify cell spacing. Hematoxylin content was measured to determine nucleus radius. Pouring simulations were conducted to generate one-hundred 3D models containing volumes of equivalent cell spacing and nuclei radius to those in histopathological samples. The nuclei radius distributions of non-tumoral and cancerous regions appearing in the same slide were significantly different (p textless 0.01) in all samples analyzed. The median nuclear-cytoplasmic ratio was 0.36 for non-tumoral cells and 0.50 for cancerous cells. The average cellular and nucleus packing densities in the 3D models generated were 65.9% (SD: 1.5%) and 13.3% (SD: 0.3%) respectively. Software to determine cell spacing and nuclei radius from histopathological samples was developed. 3D digital tissue models containing volumes with equivalent cell spacing, nucleus radius, and packing density to cancerous tissues were generated.},
keywords = {Algorithms, Cell Nucleus, Cellular dosimetry, Histopathology, Humans, Microdosimetry, Patient-specific, Radiometry},
pubstate = {published},
tppubtype = {article}
}
The biological effects of ionizing radiation depend on the tissue, tumor type, radiation quality, and patient-specific factors. Inter-patient variation in cell/nucleus size may influence patient-specific dose response. However, this variability in dose response is not well investigated due to lack of available cell/nucleus size data. The aim of this study was to develop methods to derive cell/nucleus size distributions from digital images of 2D histopathological samples and use them to build digital 3D models for use in cellular dosimetry. Nineteen of sixty hematoxylin and eosin stained lung adenocarcinoma samples investigated passed exclusion criterion to be analyzed in the study. A difference of gaussians blob detection algorithm was used to identify nucleus centers and quantify cell spacing. Hematoxylin content was measured to determine nucleus radius. Pouring simulations were conducted to generate one-hundred 3D models containing volumes of equivalent cell spacing and nuclei radius to those in histopathological samples. The nuclei radius distributions of non-tumoral and cancerous regions appearing in the same slide were significantly different (p textless 0.01) in all samples analyzed. The median nuclear-cytoplasmic ratio was 0.36 for non-tumoral cells and 0.50 for cancerous cells. The average cellular and nucleus packing densities in the 3D models generated were 65.9% (SD: 1.5%) and 13.3% (SD: 0.3%) respectively. Software to determine cell spacing and nuclei radius from histopathological samples was developed. 3D digital tissue models containing volumes with equivalent cell spacing, nucleus radius, and packing density to cancerous tissues were generated.
2020
Fast mixed integer optimization (FMIO) for high dose rate brachytherapy Journal Article
In: Physics in Medicine and Biology, vol. 65, no. 21, pp. 215005, 2020, ISSN: 1361-6560.
@article{antaki_fast_2020,
title = {Fast mixed integer optimization (FMIO) for high dose rate brachytherapy},
author = {Majd Antaki and Christopher L Deufel and Shirin A. Enger},
doi = {10.1088/1361-6560/aba317},
issn = {1361-6560},
year = {2020},
date = {2020-12-01},
journal = {Physics in Medicine and Biology},
volume = {65},
number = {21},
pages = {215005},
abstract = {The purpose of this work was to develop an efficient quadratic mixed integer programming algorithm for high dose rate (HDR) brachytherapy treatment planning problems and integrate the algorithm into an open-source Monte Carlo based treatment planning software, RapidBrachyMCTPS. The mixed-integer algorithm yields a globally optimum solution to the dose volume histogram (DVH) based problem and, unlike other methods, is not susceptible to local minimum trapping. A hybrid linear-quadratic penalty model coupled to a mixed integer programming model was used to optimize treatment plans for 10 prostate cancer patients. Dose distributions for each dwell position were calculated with RapidBrachyMCTPS with type A uncertainties less than 0.2% in voxels within the planning target volume (PTV). The optimization process was divided into two parts. First, the data was preprocessed, in which the problem size was reduced by eliminating voxels that had negligible impact on the solution (e.g. far from the dwell position). Second, the best combination of dwell times to obtain a plan with the highest score was found. The dwell positions and dose volume constraints were used as input to a commercial mixed integer optimizer (Gurobi Optimization, Inc.). A penalty-based criterion was adopted for the scoring. The voxel-reduction technique successfully reduced the problem size by an average of 91%, without loss of quality. The preprocessing of the optimization process required on average 4 s and solving for the global maximum required on average 33 s. The total optimization time averaged 37 s, which is a substantial improvement over the ∼15 min optimization time reported in published literature. The plan quality was evaluated by evaluating dose volume metrics, including PTV D90, rectum and bladder D1cc and urethra D0.1cc. In conclusion, fast mixed integer optimization is an order of magnitude faster than current mixed-integer approaches for solving HDR brachytherapy treatment planning problems with DVH based metrics.},
keywords = {Algorithms, Brachytherapy, Computer-Assisted, Humans, Linear Models, Male, Monte Carlo Method, Prostatic Neoplasms, Radiation Dosage, Radiotherapy Dosage, Radiotherapy Planning, Software, Time Factors},
pubstate = {published},
tppubtype = {article}
}
The purpose of this work was to develop an efficient quadratic mixed integer programming algorithm for high dose rate (HDR) brachytherapy treatment planning problems and integrate the algorithm into an open-source Monte Carlo based treatment planning software, RapidBrachyMCTPS. The mixed-integer algorithm yields a globally optimum solution to the dose volume histogram (DVH) based problem and, unlike other methods, is not susceptible to local minimum trapping. A hybrid linear-quadratic penalty model coupled to a mixed integer programming model was used to optimize treatment plans for 10 prostate cancer patients. Dose distributions for each dwell position were calculated with RapidBrachyMCTPS with type A uncertainties less than 0.2% in voxels within the planning target volume (PTV). The optimization process was divided into two parts. First, the data was preprocessed, in which the problem size was reduced by eliminating voxels that had negligible impact on the solution (e.g. far from the dwell position). Second, the best combination of dwell times to obtain a plan with the highest score was found. The dwell positions and dose volume constraints were used as input to a commercial mixed integer optimizer (Gurobi Optimization, Inc.). A penalty-based criterion was adopted for the scoring. The voxel-reduction technique successfully reduced the problem size by an average of 91%, without loss of quality. The preprocessing of the optimization process required on average 4 s and solving for the global maximum required on average 33 s. The total optimization time averaged 37 s, which is a substantial improvement over the ∼15 min optimization time reported in published literature. The plan quality was evaluated by evaluating dose volume metrics, including PTV D90, rectum and bladder D1cc and urethra D0.1cc. In conclusion, fast mixed integer optimization is an order of magnitude faster than current mixed-integer approaches for solving HDR brachytherapy treatment planning problems with DVH based metrics.
In: Physica medica: PM: an international journal devoted to the applications of physics to medicine and biology: official journal of the Italian Association of Biomedical Physics (AIFB), vol. 76, pp. 92–99, 2020, ISSN: 1724-191X.
@article{carroll_cross-validation_2020,
title = {Cross-validation of a non-invasive positron detector to measure the arterial input function for pharmacokinetic modelling in dynamic positron emission tomography},
author = {Liam Carroll and Etienne Croteau and Gustavo Kertzscher and Otman Sarrhini and Vincent Turgeon and Roger Lecomte and Shirin A. Enger},
doi = {10.1016/j.ejmp.2020.06.009},
issn = {1724-191X},
year = {2020},
date = {2020-08-01},
journal = {Physica medica: PM: an international journal devoted to the applications of physics to medicine and biology: official journal of the Italian Association of Biomedical Physics (AIFB)},
volume = {76},
pages = {92--99},
abstract = {Kinetic modeling of positron emission tomography (PET) data can assess index rate of uptake, metabolism and predict disease progression more accurately than conventional static PET. However, it requires knowledge of the time-course of the arterial blood radioactivity concentration, called the arterial input function (AIF). The gold standard to acquire the AIF is by invasive means. The purpose of this study was to validate a previously developed dual readout scintillating fiber-based non-invasive positron detector, hereinafter called non-invasive detector (NID), developed to determine the AIF for dynamic PET measured from the human radial artery. The NID consisted of a 3 m long plastic scintillating fiber with each end coupled to a 5 m long transmission fiber followed by a silicon photomultiplier. The scintillating fiber was enclosed inside the grooves of a plastic cylindrical shell. Two sets of experiments were performed to test the NID against a previously validated microfluidic positron detector. A closed-loop microfluidic system combined with a wrist phantom was used. During the first experiment, the three PET radioisotopes 18F, 11C and 68Ga were tested. After optimizing the detector, a second series of tests were performed using only 18F and 11C. The maximum pulse amplitude to electronic noise ratio was 52 obtained with 11C. Linear regressions showed a linear relation between the two detectors. These preliminary results show that the NID can accurately detect positrons from a patient's wrist and has the potential to non-invasively measure the AIF during a dynamic PET scan. The accuracy of these measurements needs to be determined.},
keywords = {Algorithms, Arterial input function, Arteries, Dynamic PET, Electrons, Humans, Imaging, Non-invasive detector development, Phantoms, Positron-Emission Tomography, Scintillation},
pubstate = {published},
tppubtype = {article}
}
Kinetic modeling of positron emission tomography (PET) data can assess index rate of uptake, metabolism and predict disease progression more accurately than conventional static PET. However, it requires knowledge of the time-course of the arterial blood radioactivity concentration, called the arterial input function (AIF). The gold standard to acquire the AIF is by invasive means. The purpose of this study was to validate a previously developed dual readout scintillating fiber-based non-invasive positron detector, hereinafter called non-invasive detector (NID), developed to determine the AIF for dynamic PET measured from the human radial artery. The NID consisted of a 3 m long plastic scintillating fiber with each end coupled to a 5 m long transmission fiber followed by a silicon photomultiplier. The scintillating fiber was enclosed inside the grooves of a plastic cylindrical shell. Two sets of experiments were performed to test the NID against a previously validated microfluidic positron detector. A closed-loop microfluidic system combined with a wrist phantom was used. During the first experiment, the three PET radioisotopes 18F, 11C and 68Ga were tested. After optimizing the detector, a second series of tests were performed using only 18F and 11C. The maximum pulse amplitude to electronic noise ratio was 52 obtained with 11C. Linear regressions showed a linear relation between the two detectors. These preliminary results show that the NID can accurately detect positrons from a patient’s wrist and has the potential to non-invasively measure the AIF during a dynamic PET scan. The accuracy of these measurements needs to be determined.
Model-Based Dose Calculation Algorithms for Brachytherapy Dosimetry Journal Article
In: Seminars in Radiation Oncology, vol. 30, no. 1, pp. 77–86, 2020, ISSN: 1532-9461.
@article{enger_model-based_2020,
title = {Model-Based Dose Calculation Algorithms for Brachytherapy Dosimetry},
author = {Shirin A. Enger and Javier Vijande and Mark J. Rivard},
doi = {10.1016/j.semradonc.2019.08.006},
issn = {1532-9461},
year = {2020},
date = {2020-01-01},
journal = {Seminars in Radiation Oncology},
volume = {30},
number = {1},
pages = {77--86},
abstract = {The purpose of this study was to review the limitations of dose calculation formalisms for photon-emitting brachytherapy sources based on the American Association of Physicists in Medicine (AAPM) Task Group No. 43 (TG-43) report and to provide recommendations to transition to model-based dose calculation algorithms. Additionally, an overview of these algorithms and approaches is presented. The influence of tissue and seed/applicator heterogeneities on brachytherapy dose distributions for breast, gynecologic, head and neck, rectum, and prostate cancers as well as eye plaques and electronic brachytherapy treatments were investigated by comparing dose calculations based on the TG-43 formalism and model-based dose calculation algorithms.},
keywords = {Algorithms, Brachytherapy, Computer-Assisted, Female, Humans, Male, Medical, Models, Neoplasms, Photons, Practice Guidelines as Topic, Radiometry, Radiotherapy Dosage, Radiotherapy Planning, Societies, Theoretical},
pubstate = {published},
tppubtype = {article}
}
The purpose of this study was to review the limitations of dose calculation formalisms for photon-emitting brachytherapy sources based on the American Association of Physicists in Medicine (AAPM) Task Group No. 43 (TG-43) report and to provide recommendations to transition to model-based dose calculation algorithms. Additionally, an overview of these algorithms and approaches is presented. The influence of tissue and seed/applicator heterogeneities on brachytherapy dose distributions for breast, gynecologic, head and neck, rectum, and prostate cancers as well as eye plaques and electronic brachytherapy treatments were investigated by comparing dose calculations based on the TG-43 formalism and model-based dose calculation algorithms.
2018
The influence of tissue composition uncertainty on dose distributions in brachytherapy Journal Article
In: Radiotherapy and Oncology: Journal of the European Society for Therapeutic Radiology and Oncology, vol. 126, no. 3, pp. 394–410, 2018, ISSN: 1879-0887.
@article{mann-krzisnik_influence_2018,
title = {The influence of tissue composition uncertainty on dose distributions in brachytherapy},
author = {Dylan Mann-Krzisnik and Frank Verhaegen and Shirin A. Enger},
doi = {10.1016/j.radonc.2018.01.007},
issn = {1879-0887},
year = {2018},
date = {2018-03-01},
journal = {Radiotherapy and Oncology: Journal of the European Society for Therapeutic Radiology and Oncology},
volume = {126},
number = {3},
pages = {394--410},
abstract = {BACKGROUND AND PURPOSE: Model-based dose calculation algorithms (MBDCAs) have evolved from serving as a research tool into clinical practice in brachytherapy. This study investigates primary sources of tissue elemental compositions used as input to MBDCAs and the impact of their variability on MBDCA-based dosimetry.
MATERIALS AND METHODS: Relevant studies were retrieved through PubMed. Minimum dose delivered to 90% of the target (D90), minimum dose delivered to the hottest specified volume for organs at risk (OAR) and mass energy-absorption coefficients (μen/ρ) generated by using EGSnrc "g" user-code were compared to assess the impact of compositional variability.
RESULTS: Elemental composition for hydrogen, carbon, oxygen and nitrogen are derived from the gross contents of fats, proteins and carbohydrates for any given tissue, the compositions of which are taken from literature dating back to 1940-1950. Heavier elements are derived from studies performed in the 1950-1960. Variability in elemental composition impacts greatly D90 for target tissues and doses to OAR for brachytherapy with low energy sources and less for 192Ir-based brachytherapy. Discrepancies in μen/ρ are also indicative of dose differences.
CONCLUSIONS: Updated elemental compositions are needed to optimize MBDCA-based dosimetry. Until then, tissue compositions based on gross simplifications in early studies will dominate the uncertainties in tissue heterogeneity.},
keywords = {Algorithms, Body Composition, Brachytherapy, Elemental composition, Humans, Mass energy-absorption coefficient, MBDCA, Organs at Risk, Radiotherapy Dosage, Review, Tissue heterogeneity, Uncertainty},
pubstate = {published},
tppubtype = {article}
}
BACKGROUND AND PURPOSE: Model-based dose calculation algorithms (MBDCAs) have evolved from serving as a research tool into clinical practice in brachytherapy. This study investigates primary sources of tissue elemental compositions used as input to MBDCAs and the impact of their variability on MBDCA-based dosimetry.
MATERIALS AND METHODS: Relevant studies were retrieved through PubMed. Minimum dose delivered to 90% of the target (D90), minimum dose delivered to the hottest specified volume for organs at risk (OAR) and mass energy-absorption coefficients (μen/ρ) generated by using EGSnrc “g” user-code were compared to assess the impact of compositional variability.
RESULTS: Elemental composition for hydrogen, carbon, oxygen and nitrogen are derived from the gross contents of fats, proteins and carbohydrates for any given tissue, the compositions of which are taken from literature dating back to 1940-1950. Heavier elements are derived from studies performed in the 1950-1960. Variability in elemental composition impacts greatly D90 for target tissues and doses to OAR for brachytherapy with low energy sources and less for 192Ir-based brachytherapy. Discrepancies in μen/ρ are also indicative of dose differences.
CONCLUSIONS: Updated elemental compositions are needed to optimize MBDCA-based dosimetry. Until then, tissue compositions based on gross simplifications in early studies will dominate the uncertainties in tissue heterogeneity.
MATERIALS AND METHODS: Relevant studies were retrieved through PubMed. Minimum dose delivered to 90% of the target (D90), minimum dose delivered to the hottest specified volume for organs at risk (OAR) and mass energy-absorption coefficients (μen/ρ) generated by using EGSnrc “g” user-code were compared to assess the impact of compositional variability.
RESULTS: Elemental composition for hydrogen, carbon, oxygen and nitrogen are derived from the gross contents of fats, proteins and carbohydrates for any given tissue, the compositions of which are taken from literature dating back to 1940-1950. Heavier elements are derived from studies performed in the 1950-1960. Variability in elemental composition impacts greatly D90 for target tissues and doses to OAR for brachytherapy with low energy sources and less for 192Ir-based brachytherapy. Discrepancies in μen/ρ are also indicative of dose differences.
CONCLUSIONS: Updated elemental compositions are needed to optimize MBDCA-based dosimetry. Until then, tissue compositions based on gross simplifications in early studies will dominate the uncertainties in tissue heterogeneity.
2017
Microdosimetry calculations for monoenergetic electrons using Geant4-DNA combined with a weighted track sampling algorithm Journal Article
In: Physics in Medicine and Biology, vol. 62, no. 13, pp. 5495–5508, 2017, ISSN: 1361-6560.
@article{famulari_microdosimetry_2017,
title = {Microdosimetry calculations for monoenergetic electrons using Geant4-DNA combined with a weighted track sampling algorithm},
author = {Gabriel Famulari and Piotr Pater and Shirin A. Enger},
doi = {10.1088/1361-6560/aa71f6},
issn = {1361-6560},
year = {2017},
date = {2017-07-01},
journal = {Physics in Medicine and Biology},
volume = {62},
number = {13},
pages = {5495--5508},
abstract = {The aim of this study was to calculate microdosimetric distributions for low energy electrons simulated using the Monte Carlo track structure code Geant4-DNA. Tracks for monoenergetic electrons with kinetic energies ranging from 100 eV to 1 MeV were simulated in an infinite spherical water phantom using the Geant4-DNA extension included in Geant4 toolkit version 10.2 (patch 02). The microdosimetric distributions were obtained through random sampling of transfer points and overlaying scoring volumes within the associated volume of the tracks. Relative frequency distributions of energy deposition f(textgreaterE)/f(textgreater0) and dose mean lineal energy ([Formula: see text]) values were calculated in nanometer-sized spherical and cylindrical targets. The effects of scoring volume and scoring techniques were examined. The results were compared with published data generated using MOCA8B and KURBUC. Geant4-DNA produces a lower frequency of higher energy deposits than MOCA8B. The [Formula: see text] values calculated with Geant4-DNA are smaller than those calculated using MOCA8B and KURBUC. The differences are mainly due to the lower ionization and excitation cross sections of Geant4-DNA for low energy electrons. To a lesser extent, discrepancies can also be attributed to the implementation in this study of a new and fast scoring technique that differs from that used in previous studies. For the same mean chord length ([Formula: see text]), the [Formula: see text] calculated in cylindrical volumes are larger than those calculated in spherical volumes. The discrepancies due to cross sections and scoring geometries increase with decreasing scoring site dimensions. A new set of [Formula: see text] values has been presented for monoenergetic electrons using a fast track sampling algorithm and the most recent physics models implemented in Geant4-DNA. This dataset can be combined with primary electron spectra to predict the radiation quality of photon and electron beams.},
keywords = {Algorithms, DNA, DNA Damage, Electrons, Imaging, Monte Carlo Method, Phantoms, Photons, Radiometry},
pubstate = {published},
tppubtype = {article}
}
The aim of this study was to calculate microdosimetric distributions for low energy electrons simulated using the Monte Carlo track structure code Geant4-DNA. Tracks for monoenergetic electrons with kinetic energies ranging from 100 eV to 1 MeV were simulated in an infinite spherical water phantom using the Geant4-DNA extension included in Geant4 toolkit version 10.2 (patch 02). The microdosimetric distributions were obtained through random sampling of transfer points and overlaying scoring volumes within the associated volume of the tracks. Relative frequency distributions of energy deposition f(textgreaterE)/f(textgreater0) and dose mean lineal energy ([Formula: see text]) values were calculated in nanometer-sized spherical and cylindrical targets. The effects of scoring volume and scoring techniques were examined. The results were compared with published data generated using MOCA8B and KURBUC. Geant4-DNA produces a lower frequency of higher energy deposits than MOCA8B. The [Formula: see text] values calculated with Geant4-DNA are smaller than those calculated using MOCA8B and KURBUC. The differences are mainly due to the lower ionization and excitation cross sections of Geant4-DNA for low energy electrons. To a lesser extent, discrepancies can also be attributed to the implementation in this study of a new and fast scoring technique that differs from that used in previous studies. For the same mean chord length ([Formula: see text]), the [Formula: see text] calculated in cylindrical volumes are larger than those calculated in spherical volumes. The discrepancies due to cross sections and scoring geometries increase with decreasing scoring site dimensions. A new set of [Formula: see text] values has been presented for monoenergetic electrons using a fast track sampling algorithm and the most recent physics models implemented in Geant4-DNA. This dataset can be combined with primary electron spectra to predict the radiation quality of photon and electron beams.
2015
Determination of subcellular compartment sizes for estimating dose variations in radiotherapy Journal Article
In: Radiation Protection Dosimetry, vol. 166, no. 1-4, pp. 361–364, 2015, ISSN: 1742-3406.
@article{poole_determination_2015,
title = {Determination of subcellular compartment sizes for estimating dose variations in radiotherapy},
author = {Christopher M. Poole and Anders Ahnesjö and Shirin A. Enger},
doi = {10.1093/rpd/ncv305},
issn = {1742-3406},
year = {2015},
date = {2015-09-01},
journal = {Radiation Protection Dosimetry},
volume = {166},
number = {1-4},
pages = {361--364},
abstract = {The variation in specific energy absorbed to different cell compartments caused by variations in size and chemical composition is poorly investigated in radiotherapy. The aim of this study was to develop an algorithm to derive cell and cell nuclei size distributions from 2D histology samples, and build 3D cellular geometries to provide Monte Carlo (MC)-based dose calculation engines with a morphologically relevant input geometry. Stained and unstained regions of the histology samples are segmented using a Gaussian mixture model, and individual cell nuclei are identified via thresholding. Delaunay triangulation is applied to determine the distribution of distances between the centroids of nearest neighbour cells. A pouring simulation is used to build a 3D virtual tissue sample, with cell radii randomised according to the cell size distribution determined from the histology samples. A slice with the same thickness as the histology sample is cut through the 3D data and characterised in the same way as the measured histology. The comparison between this virtual slice and the measured histology is used to adjust the initial cell size distribution into the pouring simulation. This iterative approach of a pouring simulation with adjustments guided by comparison is continued until an input cell size distribution is found that yields a distribution in the sliced geometry that agrees with the measured histology samples. The thus obtained morphologically realistic 3D cellular geometry can be used as input to MC-based dose calculation programs for studies of dose response due to variations in morphology and size of tumour/healthy tissue cells/nuclei, and extracellular material.},
keywords = {Algorithms, Breast Neoplasms, Cell Nucleus, Computer Simulation, Computer-Assisted, ErbB-2, Female, Humans, Image Processing, Imaging, Immunoenzyme Techniques, Male, Monte Carlo Method, Prostatic Neoplasms, Radiotherapy Dosage, Radiotherapy Planning, Receptor, Signal Processing, Subcellular Fractions, Three-Dimensional},
pubstate = {published},
tppubtype = {article}
}
The variation in specific energy absorbed to different cell compartments caused by variations in size and chemical composition is poorly investigated in radiotherapy. The aim of this study was to develop an algorithm to derive cell and cell nuclei size distributions from 2D histology samples, and build 3D cellular geometries to provide Monte Carlo (MC)-based dose calculation engines with a morphologically relevant input geometry. Stained and unstained regions of the histology samples are segmented using a Gaussian mixture model, and individual cell nuclei are identified via thresholding. Delaunay triangulation is applied to determine the distribution of distances between the centroids of nearest neighbour cells. A pouring simulation is used to build a 3D virtual tissue sample, with cell radii randomised according to the cell size distribution determined from the histology samples. A slice with the same thickness as the histology sample is cut through the 3D data and characterised in the same way as the measured histology. The comparison between this virtual slice and the measured histology is used to adjust the initial cell size distribution into the pouring simulation. This iterative approach of a pouring simulation with adjustments guided by comparison is continued until an input cell size distribution is found that yields a distribution in the sliced geometry that agrees with the measured histology samples. The thus obtained morphologically realistic 3D cellular geometry can be used as input to MC-based dose calculation programs for studies of dose response due to variations in morphology and size of tumour/healthy tissue cells/nuclei, and extracellular material.
2011
Modeling a hypothetical 170Tm source for brachytherapy applications Journal Article
In: Medical Physics, vol. 38, no. 10, pp. 5307–5310, 2011, ISSN: 0094-2405.
@article{enger_modeling_2011,
title = {Modeling a hypothetical 170Tm source for brachytherapy applications},
author = {Shirin A. Enger and Michel D'Amours and Luc Beaulieu},
doi = {10.1118/1.3626482},
issn = {0094-2405},
year = {2011},
date = {2011-10-01},
journal = {Medical Physics},
volume = {38},
number = {10},
pages = {5307--5310},
abstract = {PURPOSE: To perform absorbed dose calculations based on Monte Carlo simulations for a hypothetical (170)Tm source and to investigate the influence of encapsulating material on the energy spectrum of the emitted electrons and photons.
METHODS: GEANT4 Monte Carlo code version 9.2 patch 2 was used to simulate the decay process of (170)Tm and to calculate the absorbed dose distribution using the GEANT4 Penelope physics models. A hypothetical (170)Tm source based on the Flexisource brachytherapy design with the active core set as a pure thulium cylinder (length 3.5 mm and diameter 0.6 mm) and different cylindrical source encapsulations (length 5 mm and thickness 0.125 mm) constructed of titanium, stainless-steel, gold, or platinum were simulated. The radial dose function for the line source approximation was calculated following the TG-43U1 formalism for the stainless-steel encapsulation.
RESULTS: For the titanium and stainless-steel encapsulation, 94% of the total bremsstrahlung is produced inside the core, 4.8 and 5.5% in titanium and stainless-steel capsules, respectively, and less than 1% in water. For the gold capsule, 85% is produced inside the core, 14.2% inside the gold capsule, and a negligible amount (textless1%) in water. Platinum encapsulation resulted in bremsstrahlung effects similar to those with the gold encapsulation. The range of the beta particles decreases by 1.1 mm with the stainless-steel encapsulation compared to the bare source but the tissue will still receive dose from the beta particles several millimeters from the source capsule. The gold and platinum capsules not only absorb most of the electrons but also attenuate low energy photons. The mean energy of the photons escaping the core and the stainless-steel capsule is 113 keV while for the gold and platinum the mean energy is 160 keV and 165 keV, respectively.
CONCLUSIONS: A (170)Tm source is primarily a bremsstrahlung source, with the majority of bremsstrahlung photons being generated in the source core and experiencing little attenuation in the source encapsulation. Electrons are efficiently absorbed by the gold and platinum encapsulations. However, for the stainless-steel capsule (or other lower Z encapsulations) electrons will escape. The dose from these electrons is dominant over the photon dose in the first few millimeter but is not taken into account by current standard treatment planning systems. The total energy spectrum of photons emerging from the source depends on the encapsulation composition and results in mean photon energies well above 100 keV. This is higher than the main gamma-ray energy peak at 84 keV. Based on our results, the use of (170)Tm as a brachytherapy source presents notable challenges.},
keywords = {Algorithms, Brachytherapy, Computer Simulation, Computer-Assisted, Electrons, Equipment Design, Gold, Humans, Models, Monte Carlo Method, Photons, Platinum, Radioisotopes, Radiotherapy Planning, Stainless Steel, Theoretical, Thulium, Titanium},
pubstate = {published},
tppubtype = {article}
}
PURPOSE: To perform absorbed dose calculations based on Monte Carlo simulations for a hypothetical (170)Tm source and to investigate the influence of encapsulating material on the energy spectrum of the emitted electrons and photons.
METHODS: GEANT4 Monte Carlo code version 9.2 patch 2 was used to simulate the decay process of (170)Tm and to calculate the absorbed dose distribution using the GEANT4 Penelope physics models. A hypothetical (170)Tm source based on the Flexisource brachytherapy design with the active core set as a pure thulium cylinder (length 3.5 mm and diameter 0.6 mm) and different cylindrical source encapsulations (length 5 mm and thickness 0.125 mm) constructed of titanium, stainless-steel, gold, or platinum were simulated. The radial dose function for the line source approximation was calculated following the TG-43U1 formalism for the stainless-steel encapsulation.
RESULTS: For the titanium and stainless-steel encapsulation, 94% of the total bremsstrahlung is produced inside the core, 4.8 and 5.5% in titanium and stainless-steel capsules, respectively, and less than 1% in water. For the gold capsule, 85% is produced inside the core, 14.2% inside the gold capsule, and a negligible amount (textless1%) in water. Platinum encapsulation resulted in bremsstrahlung effects similar to those with the gold encapsulation. The range of the beta particles decreases by 1.1 mm with the stainless-steel encapsulation compared to the bare source but the tissue will still receive dose from the beta particles several millimeters from the source capsule. The gold and platinum capsules not only absorb most of the electrons but also attenuate low energy photons. The mean energy of the photons escaping the core and the stainless-steel capsule is 113 keV while for the gold and platinum the mean energy is 160 keV and 165 keV, respectively.
CONCLUSIONS: A (170)Tm source is primarily a bremsstrahlung source, with the majority of bremsstrahlung photons being generated in the source core and experiencing little attenuation in the source encapsulation. Electrons are efficiently absorbed by the gold and platinum encapsulations. However, for the stainless-steel capsule (or other lower Z encapsulations) electrons will escape. The dose from these electrons is dominant over the photon dose in the first few millimeter but is not taken into account by current standard treatment planning systems. The total energy spectrum of photons emerging from the source depends on the encapsulation composition and results in mean photon energies well above 100 keV. This is higher than the main gamma-ray energy peak at 84 keV. Based on our results, the use of (170)Tm as a brachytherapy source presents notable challenges.
METHODS: GEANT4 Monte Carlo code version 9.2 patch 2 was used to simulate the decay process of (170)Tm and to calculate the absorbed dose distribution using the GEANT4 Penelope physics models. A hypothetical (170)Tm source based on the Flexisource brachytherapy design with the active core set as a pure thulium cylinder (length 3.5 mm and diameter 0.6 mm) and different cylindrical source encapsulations (length 5 mm and thickness 0.125 mm) constructed of titanium, stainless-steel, gold, or platinum were simulated. The radial dose function for the line source approximation was calculated following the TG-43U1 formalism for the stainless-steel encapsulation.
RESULTS: For the titanium and stainless-steel encapsulation, 94% of the total bremsstrahlung is produced inside the core, 4.8 and 5.5% in titanium and stainless-steel capsules, respectively, and less than 1% in water. For the gold capsule, 85% is produced inside the core, 14.2% inside the gold capsule, and a negligible amount (textless1%) in water. Platinum encapsulation resulted in bremsstrahlung effects similar to those with the gold encapsulation. The range of the beta particles decreases by 1.1 mm with the stainless-steel encapsulation compared to the bare source but the tissue will still receive dose from the beta particles several millimeters from the source capsule. The gold and platinum capsules not only absorb most of the electrons but also attenuate low energy photons. The mean energy of the photons escaping the core and the stainless-steel capsule is 113 keV while for the gold and platinum the mean energy is 160 keV and 165 keV, respectively.
CONCLUSIONS: A (170)Tm source is primarily a bremsstrahlung source, with the majority of bremsstrahlung photons being generated in the source core and experiencing little attenuation in the source encapsulation. Electrons are efficiently absorbed by the gold and platinum encapsulations. However, for the stainless-steel capsule (or other lower Z encapsulations) electrons will escape. The dose from these electrons is dominant over the photon dose in the first few millimeter but is not taken into account by current standard treatment planning systems. The total energy spectrum of photons emerging from the source depends on the encapsulation composition and results in mean photon energies well above 100 keV. This is higher than the main gamma-ray energy peak at 84 keV. Based on our results, the use of (170)Tm as a brachytherapy source presents notable challenges.
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.
@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.