2022
Carroll, Liam; Enger, Shirin A.
Monte Carlo Simulations of a Non-Invasive Positron Detector to Measure the Arterial Input Function for Dynamic PET Proceedings Article
In: Journal of Physics: Conference Series, pp. 012005, IOP Publishing 2022.
BibTeX | Tags:
@inproceedings{carroll2022monte,
title = {Monte Carlo Simulations of a Non-Invasive Positron Detector to Measure the Arterial Input Function for Dynamic PET},
author = {Liam Carroll and Shirin A. Enger},
year = {2022},
date = {2022-01-01},
urldate = {2022-01-01},
booktitle = {Journal of Physics: Conference Series},
volume = {2167},
number = {1},
pages = {012005},
organization = {IOP Publishing},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Carroll, Liam; Enger, Shirin A
Simulation of a novel, non-invasive radiation detector to measure the arterial input function for dynamic PET Journal Article
In: Medical Physics, 2022.
BibTeX | Tags:
@article{carroll2022simulation,
title = {Simulation of a novel, non-invasive radiation detector to measure the arterial input function for dynamic PET},
author = {Liam Carroll and Shirin A Enger},
year = {2022},
date = {2022-01-01},
journal = {Medical Physics},
publisher = {Wiley Online Library},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
2021
Weishaupt, Luca L.
T I Gurman Prize in Physics award
2021.
Abstract | Links | BibTeX | Tags:
@award{Weishaupt2021,
title = {T I Gurman Prize in Physics},
author = {Luca L. Weishaupt},
url = {http://scholarships.studentscholarships.org/t_i_gurman_prize_2236.php},
year = {2021},
date = {2021-09-01},
urldate = {2021-09-01},
organization = {McGill University},
abstract = {Established in 1997 by friends and family of T.I. Gurman in honour of his 95th birthday. Awarded by the Faculty of Science Scholarships Committee on the recommendation of the Department of Physics to a student with high academic standing entering the final year in a Major program in Physics.},
howpublished = {McGill University},
keywords = {},
pubstate = {published},
tppubtype = {award}
}
Established in 1997 by friends and family of T.I. Gurman in honour of his 95th birthday. Awarded by the Faculty of Science Scholarships Committee on the recommendation of the Department of Physics to a student with high academic standing entering the final year in a Major program in Physics.
Thibodeau-Antonacci, Alana
Canada Graduate Scholarship – Doctoral Program award
2021.
@award{Thibodeau-Antonacci2021d,
title = {Canada Graduate Scholarship – Doctoral Program},
author = {Alana Thibodeau-Antonacci},
url = {https://www.nserc-crsng.gc.ca/students-etudiants/pg-cs/cgsd-bescd_eng.asp},
year = {2021},
date = {2021-09-01},
organization = {NSERC},
keywords = {},
pubstate = {published},
tppubtype = {award}
}
Esmaelbeigi, Azin
Biological & Biomedical Engineering PhD Recruitment Award award
2021.
@award{nokey,
title = {Biological & Biomedical Engineering PhD Recruitment Award },
author = {Azin Esmaelbeigi},
url = {https://www.mcgill.ca/bbme/programs/funding#BME-Recruitment-Award},
year = {2021},
date = {2021-09-01},
keywords = {},
pubstate = {published},
tppubtype = {award}
}
Kalinowski, Jonathan
Merit-based recruitment award for first year MSc students. award
2021.
BibTeX | Tags:
@award{nokey,
title = {Merit-based recruitment award for first year MSc students.},
author = {Jonathan Kalinowski},
year = {2021},
date = {2021-09-01},
urldate = {2021-09-01},
organization = {McGill Medical Physics Unit},
keywords = {},
pubstate = {published},
tppubtype = {award}
}
Weishaupt, Luca L.; Thibodeau-Antonacci, Alana; Garant, Aurelie; Singh, Kelita; Miller, Corey; Vuong, Té; Enger, Shirin A.
Deep learning based tumor segmentation of endoscopy images for rectal cancer patients Presentation
ESTRO Annual meeting, 27.08.2021.
Abstract | Links | BibTeX | Tags: artificial intelligence, Deep Learning, endoscopy, tumor detection
@misc{Weishaupt2021b,
title = {Deep learning based tumor segmentation of endoscopy images for rectal cancer patients},
author = {Luca L. Weishaupt and Alana Thibodeau-Antonacci and Aurelie Garant and Kelita Singh and Corey Miller and Té Vuong and Shirin A. Enger},
url = {https://www.estro.org/Congresses/ESTRO-2021/610/posterdiscussion34-deep-learningforauto-contouring/3710/deeplearning-basedtumorsegmentationofendoscopyimag},
year = {2021},
date = {2021-08-27},
urldate = {2021-08-27},
abstract = {Purpose or Objective
The objective of this study was to develop an automated rectal tumor segmentation algorithm from endoscopy images. The algorithm will be used in a future multimodal treatment outcome prediction model. Currently, treatment outcome prediction models rely on manual segmentations of regions of interest, which are prone to inter-observer variability. To quantify this human error and demonstrate the feasibility of automated endoscopy image segmentation, we compare three deep learning architectures.
Material and Methods
A gastrointestinal physician (G1) segmented 550 endoscopy images of rectal tumors into tumor and non-tumor regions. To quantify the inter-observer variability, a second gastrointestinal physician (G2) contoured 319 of the images independently.
The 550 images and annotations from G1 were divided into 408 training, 82 validation, and 60 testing sets. Three deep learning architectures were trained; a fully convolutional neural network (FCN32), a U-Net, and a SegNet. These architectures have been used for robust medical image segmentation in previous studies.
All models were trained on a CPU supercomputing cluster. Data augmentation in the form of random image transformations, including scaling, rotation, shearing, Gaussian blurring, and noise addition, was used to improve the models' robustness.
The neural networks' output went through a final layer of noise removal and hole filling before evaluation. Finally, the segmentations from G2 and the neural networks' predictions were compared against the ground truth labels from G1.
Results
The FCN32, U-Net, and SegNet had average segmentation times of 0.77, 0.48, and 0.43 seconds per image, respectively. The average segmentation time per image for G1 and G2 were 10 and 8 seconds, respectively.
All the ground truth labels contained tumors, but G2 and the deep learning models did not always find tumors in the images. The scores are based on the agreement of tumor contours with G1’s ground truth and were thus only computed for images in which tumor was found. The automated segmentation algorithms consistently achieved equal or better scores than G2's manual segmentations. G2's low F1/DICE and precision scores indicate poor agreement between the manual contours.
Conclusion
There is a need for robust and accurate segmentation algorithms for rectal tumor segmentation since manual segmentation of these tumors is susceptible to significant inter-observer variability. The deep learning-based segmentation algorithms proposed in this study are more efficient and achieved a higher agreement with our manual ground truth segmentations than a second expert annotator. Future studies will investigate how to train deep learning models on multiple ground truth annotations to prevent learning observer biases.},
howpublished = {ESTRO Annual meeting},
keywords = {artificial intelligence, Deep Learning, endoscopy, tumor detection},
pubstate = {published},
tppubtype = {presentation}
}
Purpose or Objective
The objective of this study was to develop an automated rectal tumor segmentation algorithm from endoscopy images. The algorithm will be used in a future multimodal treatment outcome prediction model. Currently, treatment outcome prediction models rely on manual segmentations of regions of interest, which are prone to inter-observer variability. To quantify this human error and demonstrate the feasibility of automated endoscopy image segmentation, we compare three deep learning architectures.
Material and Methods
A gastrointestinal physician (G1) segmented 550 endoscopy images of rectal tumors into tumor and non-tumor regions. To quantify the inter-observer variability, a second gastrointestinal physician (G2) contoured 319 of the images independently.
The 550 images and annotations from G1 were divided into 408 training, 82 validation, and 60 testing sets. Three deep learning architectures were trained; a fully convolutional neural network (FCN32), a U-Net, and a SegNet. These architectures have been used for robust medical image segmentation in previous studies.
All models were trained on a CPU supercomputing cluster. Data augmentation in the form of random image transformations, including scaling, rotation, shearing, Gaussian blurring, and noise addition, was used to improve the models' robustness.
The neural networks' output went through a final layer of noise removal and hole filling before evaluation. Finally, the segmentations from G2 and the neural networks' predictions were compared against the ground truth labels from G1.
Results
The FCN32, U-Net, and SegNet had average segmentation times of 0.77, 0.48, and 0.43 seconds per image, respectively. The average segmentation time per image for G1 and G2 were 10 and 8 seconds, respectively.
All the ground truth labels contained tumors, but G2 and the deep learning models did not always find tumors in the images. The scores are based on the agreement of tumor contours with G1’s ground truth and were thus only computed for images in which tumor was found. The automated segmentation algorithms consistently achieved equal or better scores than G2's manual segmentations. G2's low F1/DICE and precision scores indicate poor agreement between the manual contours.
Conclusion
There is a need for robust and accurate segmentation algorithms for rectal tumor segmentation since manual segmentation of these tumors is susceptible to significant inter-observer variability. The deep learning-based segmentation algorithms proposed in this study are more efficient and achieved a higher agreement with our manual ground truth segmentations than a second expert annotator. Future studies will investigate how to train deep learning models on multiple ground truth annotations to prevent learning observer biases.
The objective of this study was to develop an automated rectal tumor segmentation algorithm from endoscopy images. The algorithm will be used in a future multimodal treatment outcome prediction model. Currently, treatment outcome prediction models rely on manual segmentations of regions of interest, which are prone to inter-observer variability. To quantify this human error and demonstrate the feasibility of automated endoscopy image segmentation, we compare three deep learning architectures.
Material and Methods
A gastrointestinal physician (G1) segmented 550 endoscopy images of rectal tumors into tumor and non-tumor regions. To quantify the inter-observer variability, a second gastrointestinal physician (G2) contoured 319 of the images independently.
The 550 images and annotations from G1 were divided into 408 training, 82 validation, and 60 testing sets. Three deep learning architectures were trained; a fully convolutional neural network (FCN32), a U-Net, and a SegNet. These architectures have been used for robust medical image segmentation in previous studies.
All models were trained on a CPU supercomputing cluster. Data augmentation in the form of random image transformations, including scaling, rotation, shearing, Gaussian blurring, and noise addition, was used to improve the models' robustness.
The neural networks' output went through a final layer of noise removal and hole filling before evaluation. Finally, the segmentations from G2 and the neural networks' predictions were compared against the ground truth labels from G1.
Results
The FCN32, U-Net, and SegNet had average segmentation times of 0.77, 0.48, and 0.43 seconds per image, respectively. The average segmentation time per image for G1 and G2 were 10 and 8 seconds, respectively.
All the ground truth labels contained tumors, but G2 and the deep learning models did not always find tumors in the images. The scores are based on the agreement of tumor contours with G1’s ground truth and were thus only computed for images in which tumor was found. The automated segmentation algorithms consistently achieved equal or better scores than G2's manual segmentations. G2's low F1/DICE and precision scores indicate poor agreement between the manual contours.
Conclusion
There is a need for robust and accurate segmentation algorithms for rectal tumor segmentation since manual segmentation of these tumors is susceptible to significant inter-observer variability. The deep learning-based segmentation algorithms proposed in this study are more efficient and achieved a higher agreement with our manual ground truth segmentations than a second expert annotator. Future studies will investigate how to train deep learning models on multiple ground truth annotations to prevent learning observer biases.
DeCunha, Joseph M.; Villegas, Fernanda; Vallières, Martin; Torres, Jose; Camilleri-Broët, Sophie; Enger, Shirin A.
Patient-specific microdosimetry: a proof of concept Journal Article
In: Physics in Medicine and Biology, 2021, ISSN: 1361-6560.
Abstract | Links | BibTeX | Tags: Biological Effectiveness, Brachytherapy, Cellular Morphology, Microdosimetry, Patient-specific
@article{decunha_patient-specific_2021,
title = {Patient-specific microdosimetry: a proof of concept},
author = {Joseph M. DeCunha and Fernanda Villegas and Martin Vallières and Jose Torres and Sophie Camilleri-Broët and Shirin A. Enger},
doi = {10.1088/1361-6560/ac1d1e},
issn = {1361-6560},
year = {2021},
date = {2021-08-01},
journal = {Physics in Medicine and Biology},
abstract = {Microscopic energy deposition distributions from ionizing radiation are used to predict the biological effects of an irradiation and vary depending on biological target size. Ionizing radiation is thought to kill cells or inhibit cell cycling mainly by damaging DNA in the cell nucleus. The size of cells and nuclei depends on tissue type, cell cycle, and malignancy, all of which vary between patients. The aim of this study was to develop methods to perform patient-specific microdosimetry, that being, determining microdosimetric quantities in volumes that correspond to the sizes of cells and nuclei observed in a patient's tissue. A histopathological sample extracted from a stage I lung adenocarcinoma patient was analyzed. A pouring simulation was used to generate a three-dimensional tissue model from cell and nucleus size information determined from the histopathological sample. Microdosimetric distributions including f(y) and d(y) were determined for Co-60,Ir-192,Yb-169 and I-125 in a patient-specific model containing a distribution of cell and nucleus sizes. Fixed radius models and a summation method (where f(y) from many fixed radii models are summed) were compared to the full patient-specific model to evaluate their suitability for fast determination of patient-specific microdosimetric parameters. Fixed radius models do not provide a close approximation of the full patient-specific model y ̅_f or y ̅_d for the lower energy sources investigated, Yb-169 and I-125. The higher energy sources investigated, Co-60 and Ir-192 are less sensitive to target size variation than Yb-169 and I-125. A summation method yields the most accurate approximation of the full model d(y) for all radioisotopes investigated. A summation method allows for the computation of patient-specific microdosimetric distributions with the computing power of a personal computer. With appropriate biological inputs the microdosimetric distributions computed using these methods can yield a patient-specific relative biological effectiveness as part of a multiscale treatment planning approach.},
keywords = {Biological Effectiveness, Brachytherapy, Cellular Morphology, Microdosimetry, Patient-specific},
pubstate = {published},
tppubtype = {article}
}
Microscopic energy deposition distributions from ionizing radiation are used to predict the biological effects of an irradiation and vary depending on biological target size. Ionizing radiation is thought to kill cells or inhibit cell cycling mainly by damaging DNA in the cell nucleus. The size of cells and nuclei depends on tissue type, cell cycle, and malignancy, all of which vary between patients. The aim of this study was to develop methods to perform patient-specific microdosimetry, that being, determining microdosimetric quantities in volumes that correspond to the sizes of cells and nuclei observed in a patient's tissue. A histopathological sample extracted from a stage I lung adenocarcinoma patient was analyzed. A pouring simulation was used to generate a three-dimensional tissue model from cell and nucleus size information determined from the histopathological sample. Microdosimetric distributions including f(y) and d(y) were determined for Co-60,Ir-192,Yb-169 and I-125 in a patient-specific model containing a distribution of cell and nucleus sizes. Fixed radius models and a summation method (where f(y) from many fixed radii models are summed) were compared to the full patient-specific model to evaluate their suitability for fast determination of patient-specific microdosimetric parameters. Fixed radius models do not provide a close approximation of the full patient-specific model y ̅_f or y ̅_d for the lower energy sources investigated, Yb-169 and I-125. The higher energy sources investigated, Co-60 and Ir-192 are less sensitive to target size variation than Yb-169 and I-125. A summation method yields the most accurate approximation of the full model d(y) for all radioisotopes investigated. A summation method allows for the computation of patient-specific microdosimetric distributions with the computing power of a personal computer. With appropriate biological inputs the microdosimetric distributions computed using these methods can yield a patient-specific relative biological effectiveness as part of a multiscale treatment planning approach.
Lecavalier-Barsoum, Magali; Khosrow-Khavar, Farzin; Asiev, Krum; Popovic, Marija; Vuong, Te; Enger, Shirin A.
Utilization of brachytherapy in Quebec, Canada Journal Article
In: Brachytherapy, pp. S1538–4721(21)00452–9, 2021, ISSN: 1873-1449.
Abstract | Links | BibTeX | Tags: High dose rate brachytherapy, Interstitial brachytherapy, Intracavitary brachytherapy, Low dose rate brachytherapy, Number of brachytherapy treatments, Trends in utilization
@article{lecavalier-barsoum_utilization_2021,
title = {Utilization of brachytherapy in Quebec, Canada},
author = {Magali Lecavalier-Barsoum and Farzin Khosrow-Khavar and Krum Asiev and Marija Popovic and Te Vuong and Shirin A. Enger},
doi = {10.1016/j.brachy.2021.07.002},
issn = {1873-1449},
year = {2021},
date = {2021-08-01},
journal = {Brachytherapy},
pages = {S1538--4721(21)00452--9},
abstract = {BACKGROUND AND PURPOSE: Despite the excellent clinical outcomes from brachytherapy treatments compared with other modalities and the low associated costs, there have been reports of a decline in utilization of brachytherapy. The aim of this study was to investigate in detail the trend in utilization of brachytherapy in the province of Québec, Canada, from 2011 to 2019.
MATERIALS AND METHODS: All radiotherapy clinics in the province of Quebec, and among these the clinics that provide brachytherapy treatments, were identified. This observational retrospective cohort study involved analysis of data compiled by the Ministère de la Santé et des Services Sociaux du Québec for the period of 2011 to end of 2019 on all brachytherapy procedures performed in the province of Quebec. Time series graphs were used to describe the number of high dose rate (HDR) and low dose rate (LDR) brachytherapy treatments during the studied time period. Statistical analysis was conducted using R statistical software.
RESULTS: Between 2011 and 2019, 12 hospitals in the province of Québec provided radiotherapy treatments, and all of them offered brachytherapy services. The median annual number of brachytherapy sessions was 4413 (range 3930-4829). HDR brachytherapy represented over 90% of all brachytherapy treatments throughout the study period. Significant changes over time were observed in the number of treatments: at least 5% change was seen only for the two most common subtypes of brachytherapy, HDR interstitial and HDR intracavitary, with an increase of 9.6% and a decrease of 9.2%, respectively. The use of other subtypes of brachytherapy (HDR-plesiotherapy, LDR-interstitial, LDR-intracavitary, LDR-eye plaque) was stable between 2011 and 2019, with ≤ 2.5% variation.
CONCLUSION: This study demonstrates an overall steady use of brachytherapy between 2011 and 2019 in Quebec. Brachytherapy offers numerous advantages for the treatment of diverse cancer sites. Although more sophisticated external beam radiotherapy treatments have emerged in the last decades, the precision and cost-effectiveness of brachytherapy remain unbeaten. To ensure the continued use and availability of brachytherapy, governments must put in place policies and regulations to that effect. Training and exposure of future health care professionals to brachytherapy within Quebec and Canada is essential to provide all patients the same access to this life saving modality.},
keywords = {High dose rate brachytherapy, Interstitial brachytherapy, Intracavitary brachytherapy, Low dose rate brachytherapy, Number of brachytherapy treatments, Trends in utilization},
pubstate = {published},
tppubtype = {article}
}
BACKGROUND AND PURPOSE: Despite the excellent clinical outcomes from brachytherapy treatments compared with other modalities and the low associated costs, there have been reports of a decline in utilization of brachytherapy. The aim of this study was to investigate in detail the trend in utilization of brachytherapy in the province of Québec, Canada, from 2011 to 2019.
MATERIALS AND METHODS: All radiotherapy clinics in the province of Quebec, and among these the clinics that provide brachytherapy treatments, were identified. This observational retrospective cohort study involved analysis of data compiled by the Ministère de la Santé et des Services Sociaux du Québec for the period of 2011 to end of 2019 on all brachytherapy procedures performed in the province of Quebec. Time series graphs were used to describe the number of high dose rate (HDR) and low dose rate (LDR) brachytherapy treatments during the studied time period. Statistical analysis was conducted using R statistical software.
RESULTS: Between 2011 and 2019, 12 hospitals in the province of Québec provided radiotherapy treatments, and all of them offered brachytherapy services. The median annual number of brachytherapy sessions was 4413 (range 3930-4829). HDR brachytherapy represented over 90% of all brachytherapy treatments throughout the study period. Significant changes over time were observed in the number of treatments: at least 5% change was seen only for the two most common subtypes of brachytherapy, HDR interstitial and HDR intracavitary, with an increase of 9.6% and a decrease of 9.2%, respectively. The use of other subtypes of brachytherapy (HDR-plesiotherapy, LDR-interstitial, LDR-intracavitary, LDR-eye plaque) was stable between 2011 and 2019, with ≤ 2.5% variation.
CONCLUSION: This study demonstrates an overall steady use of brachytherapy between 2011 and 2019 in Quebec. Brachytherapy offers numerous advantages for the treatment of diverse cancer sites. Although more sophisticated external beam radiotherapy treatments have emerged in the last decades, the precision and cost-effectiveness of brachytherapy remain unbeaten. To ensure the continued use and availability of brachytherapy, governments must put in place policies and regulations to that effect. Training and exposure of future health care professionals to brachytherapy within Quebec and Canada is essential to provide all patients the same access to this life saving modality.
MATERIALS AND METHODS: All radiotherapy clinics in the province of Quebec, and among these the clinics that provide brachytherapy treatments, were identified. This observational retrospective cohort study involved analysis of data compiled by the Ministère de la Santé et des Services Sociaux du Québec for the period of 2011 to end of 2019 on all brachytherapy procedures performed in the province of Quebec. Time series graphs were used to describe the number of high dose rate (HDR) and low dose rate (LDR) brachytherapy treatments during the studied time period. Statistical analysis was conducted using R statistical software.
RESULTS: Between 2011 and 2019, 12 hospitals in the province of Québec provided radiotherapy treatments, and all of them offered brachytherapy services. The median annual number of brachytherapy sessions was 4413 (range 3930-4829). HDR brachytherapy represented over 90% of all brachytherapy treatments throughout the study period. Significant changes over time were observed in the number of treatments: at least 5% change was seen only for the two most common subtypes of brachytherapy, HDR interstitial and HDR intracavitary, with an increase of 9.6% and a decrease of 9.2%, respectively. The use of other subtypes of brachytherapy (HDR-plesiotherapy, LDR-interstitial, LDR-intracavitary, LDR-eye plaque) was stable between 2011 and 2019, with ≤ 2.5% variation.
CONCLUSION: This study demonstrates an overall steady use of brachytherapy between 2011 and 2019 in Quebec. Brachytherapy offers numerous advantages for the treatment of diverse cancer sites. Although more sophisticated external beam radiotherapy treatments have emerged in the last decades, the precision and cost-effectiveness of brachytherapy remain unbeaten. To ensure the continued use and availability of brachytherapy, governments must put in place policies and regulations to that effect. Training and exposure of future health care professionals to brachytherapy within Quebec and Canada is essential to provide all patients the same access to this life saving modality.
Bui, Alaina; Childress, Lilian; Sankey, Jack; Seuntjens, Jan; Enger, Shirin A.
Effect of Incoming Particle Energy and Ionization Cluster Size on the G-value of Hydrated Electrons Presentation
AAPM 63rd Annual Meeting, 25.07.2021.
BibTeX | Tags:
@misc{Bui2021,
title = {Effect of Incoming Particle Energy and Ionization Cluster Size on the G-value of Hydrated Electrons},
author = {Alaina Bui and Lilian Childress and Jack Sankey and Jan Seuntjens and Shirin A. Enger},
year = {2021},
date = {2021-07-25},
howpublished = {AAPM 63rd Annual Meeting},
keywords = {},
pubstate = {published},
tppubtype = {presentation}
}
Thibodeau-Antonacci, Alana; Jafarzadeh, Hossein; Carroll, Liam; Weishaupt, Luca L.
Mitacs Globalink Research Award award
2021.
Abstract | Links | BibTeX | Tags: award
@award{Thibodeau-Antonacci2021c,
title = {Mitacs Globalink Research Award},
author = {Alana Thibodeau-Antonacci and Hossein Jafarzadeh and Liam Carroll and Luca L. Weishaupt},
url = {https://www.mitacs.ca/en/programs/globalink/globalink-research-award},
year = {2021},
date = {2021-07-01},
urldate = {2021-07-01},
organization = {MITACS},
abstract = {The Mitacs Globalink Research Award (GRA) supports research collaborations between Canada and select partner organizations and eligible countries and regions. It was awarded to Alana Thibodeau-Antonacci, Hossein Jafarzadeh, Liam Carroll and Luca L. Weishaupt.
Under the joint supervision of a home and host professor, successful senior undergraduate students, graduate students, as well as postdoctoral fellows will receive a $6,000 research award to conduct a 12- to 24-week research project in the other country. Awards are offered in partnership with Mitacs’s Canadian academic partners (and, in some cases, with Mitacs’s international partners) and are subject to available funding. },
howpublished = {Mitacs},
keywords = {award},
pubstate = {published},
tppubtype = {award}
}
The Mitacs Globalink Research Award (GRA) supports research collaborations between Canada and select partner organizations and eligible countries and regions. It was awarded to Alana Thibodeau-Antonacci, Hossein Jafarzadeh, Liam Carroll and Luca L. Weishaupt.
Under the joint supervision of a home and host professor, successful senior undergraduate students, graduate students, as well as postdoctoral fellows will receive a $6,000 research award to conduct a 12- to 24-week research project in the other country. Awards are offered in partnership with Mitacs’s Canadian academic partners (and, in some cases, with Mitacs’s international partners) and are subject to available funding.
Under the joint supervision of a home and host professor, successful senior undergraduate students, graduate students, as well as postdoctoral fellows will receive a $6,000 research award to conduct a 12- to 24-week research project in the other country. Awards are offered in partnership with Mitacs’s Canadian academic partners (and, in some cases, with Mitacs’s international partners) and are subject to available funding.
Bui, Alaina; Bekerat, Hamed; Enger, Shirin A.
Film measurements for verification of dose results in hydrated electron dosimetry Presentation
COMP Virtual Scientific Meeting, 25.06.2021.
BibTeX | Tags:
@misc{Bui2021b,
title = {Film measurements for verification of dose results in hydrated electron dosimetry},
author = {Alaina Bui and Hamed Bekerat and Shirin A. Enger},
year = {2021},
date = {2021-06-25},
howpublished = {COMP Virtual Scientific Meeting},
keywords = {},
pubstate = {published},
tppubtype = {presentation}
}
Bui, Alaina; Childress, Lilian; Sankey, Jack; Seuntjens, Jan; Enger, Shirin A.
Effect of incoming particle energy, cluster size, LET, and depth in water on the G-value of hydrated electrons Presentation
COMP Virtual Scientific Meeting, 22.06.2021.
BibTeX | Tags:
@misc{Bui2021c,
title = {Effect of incoming particle energy, cluster size, LET, and depth in water on the G-value of hydrated electrons},
author = {Alaina Bui and Lilian Childress and Jack Sankey and Jan Seuntjens and Shirin A. Enger },
year = {2021},
date = {2021-06-22},
urldate = {2021-06-22},
howpublished = {COMP Virtual Scientific Meeting},
keywords = {},
pubstate = {published},
tppubtype = {presentation}
}
Weishaupt, Luca L.; Thibodeau-Antonacci, Alana; Garant, Aurelie; Singh, Kelita; Miller, Corey; Vuong, Té; Enger, Shirin A.
Inter-Observer Variability and Deep Learning in Rectal Tumor Segmentation from Endoscopy Images Presentation
The COMP Annual Scientific Meeting 2021, 22.06.2021.
@misc{Weishaupt2021c,
title = {Inter-Observer Variability and Deep Learning in Rectal Tumor Segmentation from Endoscopy Images},
author = {Luca L. Weishaupt and Alana Thibodeau-Antonacci and Aurelie Garant and Kelita Singh and Corey Miller and Té Vuong and Shirin A. Enger},
year = {2021},
date = {2021-06-22},
urldate = {2021-06-22},
abstract = {Purpose
To develop an automated rectal tumor segmentation algorithm from endoscopy images.
Material/Methods
A gastrointestinal physician (G1) segmented 2005 endoscopy images into tumor and non-tumor
regions. To quantify the inter-observer variability, a second gastrointestinal physician (G2)
contoured the images independently.
Three deep-learning architectures used for robust medical image segmentation in previous
studies were trained: a fully convolutional neural network (FCN32), a U-Net, and a SegNet.
Since the majority of the images did not contain tumors, two methods were compared for
training. Models were trained using only tumor images (M1) and all images (M2). G1’s images
and annotations were divided into 408 training, 82 validation, and 60 testing sets for M1, 1181
training, 372 validation, and 452 testing sets for M2.
Finally, segmentations from G2 and neural networks' predictions were compared against ground
truth labels from G1, and F1 scores were computed for images where both physicians found
tumors.
Results
The deep-learning segmentation took less than 1 second, while manual segmentation took
approximately 10 seconds per image.
The M1’s models consistently achieved equal or better scores (SegNet F1:0.80±0.08) than G2's
manual segmentations (F1:0.68±0.25). G2's low F1/DICE and precision scores indicate poor
agreement between the manual contours. Models from M2 achieved lower scores than G2 and
M1’s models since they demonstrated a strong bias towards predicting no tumor for all images.
Conclusion
Future studies will investigate training on an equal number of images with/without tumor, using
ground truth contours from multiple experts simultaneously.},
howpublished = {The COMP Annual Scientific Meeting 2021},
keywords = {},
pubstate = {published},
tppubtype = {presentation}
}
Purpose
To develop an automated rectal tumor segmentation algorithm from endoscopy images.
Material/Methods
A gastrointestinal physician (G1) segmented 2005 endoscopy images into tumor and non-tumor
regions. To quantify the inter-observer variability, a second gastrointestinal physician (G2)
contoured the images independently.
Three deep-learning architectures used for robust medical image segmentation in previous
studies were trained: a fully convolutional neural network (FCN32), a U-Net, and a SegNet.
Since the majority of the images did not contain tumors, two methods were compared for
training. Models were trained using only tumor images (M1) and all images (M2). G1’s images
and annotations were divided into 408 training, 82 validation, and 60 testing sets for M1, 1181
training, 372 validation, and 452 testing sets for M2.
Finally, segmentations from G2 and neural networks' predictions were compared against ground
truth labels from G1, and F1 scores were computed for images where both physicians found
tumors.
Results
The deep-learning segmentation took less than 1 second, while manual segmentation took
approximately 10 seconds per image.
The M1’s models consistently achieved equal or better scores (SegNet F1:0.80±0.08) than G2's
manual segmentations (F1:0.68±0.25). G2's low F1/DICE and precision scores indicate poor
agreement between the manual contours. Models from M2 achieved lower scores than G2 and
M1’s models since they demonstrated a strong bias towards predicting no tumor for all images.
Conclusion
Future studies will investigate training on an equal number of images with/without tumor, using
ground truth contours from multiple experts simultaneously.
To develop an automated rectal tumor segmentation algorithm from endoscopy images.
Material/Methods
A gastrointestinal physician (G1) segmented 2005 endoscopy images into tumor and non-tumor
regions. To quantify the inter-observer variability, a second gastrointestinal physician (G2)
contoured the images independently.
Three deep-learning architectures used for robust medical image segmentation in previous
studies were trained: a fully convolutional neural network (FCN32), a U-Net, and a SegNet.
Since the majority of the images did not contain tumors, two methods were compared for
training. Models were trained using only tumor images (M1) and all images (M2). G1’s images
and annotations were divided into 408 training, 82 validation, and 60 testing sets for M1, 1181
training, 372 validation, and 452 testing sets for M2.
Finally, segmentations from G2 and neural networks' predictions were compared against ground
truth labels from G1, and F1 scores were computed for images where both physicians found
tumors.
Results
The deep-learning segmentation took less than 1 second, while manual segmentation took
approximately 10 seconds per image.
The M1’s models consistently achieved equal or better scores (SegNet F1:0.80±0.08) than G2's
manual segmentations (F1:0.68±0.25). G2's low F1/DICE and precision scores indicate poor
agreement between the manual contours. Models from M2 achieved lower scores than G2 and
M1’s models since they demonstrated a strong bias towards predicting no tumor for all images.
Conclusion
Future studies will investigate training on an equal number of images with/without tumor, using
ground truth contours from multiple experts simultaneously.
Morcos, Marc; Antaki, Majd; Thibodeau-Antonacci, Alana; Kalinowski, Jonathan; Glickman, Harry; Enger, Shirin A.
RapidBrachyMCTPS: An open-source dose calculation and optimization tool for brachytherapy research Presentation
COMP, 01.06.2021.
BibTeX | Tags:
@misc{Morcos2021c,
title = {RapidBrachyMCTPS: An open-source dose calculation and optimization tool for brachytherapy research},
author = {Marc Morcos and Majd Antaki and Alana Thibodeau-Antonacci and Jonathan Kalinowski and Harry Glickman and Shirin A. Enger},
year = {2021},
date = {2021-06-01},
howpublished = {COMP},
keywords = {},
pubstate = {published},
tppubtype = {presentation}
}
Thibodeau-Antonacci, Alana; Vuong, Té; Bekerat, Hamed; Liang, Liheng; Enger, Shirin A.
2021.
Abstract | Links | BibTeX | Tags: Intensity Modulation, Intracavitary brachytherapy, Monte Carlo
@award{Thibodeau-Antonacci2021b,
title = {Development of a Dynamic Shielding Intensity-Modulated Brachytherapy Applicator for the Treatment of Rectal Cancer},
author = {Alana Thibodeau-Antonacci and Té Vuong and Hamed Bekerat and Liheng Liang and Shirin A. Enger},
url = {https://curietherapi.es/},
year = {2021},
date = {2021-05-23},
urldate = {2021-05-23},
organization = {Curietherapies},
abstract = {Oral presentation given online at the annual congress of Curietherapies https://curietherapi.es/},
howpublished = {Annual Congress of Curietherapies},
keywords = {Intensity Modulation, Intracavitary brachytherapy, Monte Carlo},
pubstate = {published},
tppubtype = {award}
}
Oral presentation given online at the annual congress of Curietherapies https://curietherapi.es/
Behmand, Behnaz; Evans, Michael D. C.; Kamio, Yuji; Enger, Shirin A.
Correlation between Radiation-induced Foci from 192Ir Brachytherapy and Tumor Nuclei Size Presentation
World Congress of Brachytherapy (WCB) - Online, 06.05.2021.
BibTeX | Tags:
@misc{Behmand2021,
title = {Correlation between Radiation-induced Foci from 192Ir Brachytherapy and Tumor Nuclei Size},
author = {Behnaz Behmand and Michael D. C. Evans and Yuji Kamio and Shirin A. Enger},
year = {2021},
date = {2021-05-06},
howpublished = {World Congress of Brachytherapy (WCB) - Online},
keywords = {},
pubstate = {published},
tppubtype = {presentation}
}
Morcos, Marc; Viswanathan, Akila N.; Enger, Shirin A.
In: Medical Physics, vol. 48, no. 5, pp. 2604–2613, 2021, ISSN: 2473-4209.
Abstract | Links | BibTeX | Tags: Brachytherapy, Computer-Assisted, dynamic shield brachytherapy, Female, Humans, IMBT, Intensity modulated brachytherapy, Iridium Radioisotopes, Monte Carlo Method, MR-guided brachytherapy, Radiotherapy Dosage, Radiotherapy Planning, rotating shield brachytherapy, RSBT, Uterine Cervical Neoplasms
@article{morcos_impact_2021,
title = {On the impact of absorbed dose specification, tissue heterogeneities, and applicator heterogeneities on Monte Carlo-based dosimetry of Ir-192, Se-75, and Yb-169 in conventional and intensity-modulated brachytherapy for the treatment of cervical cancer},
author = {Marc Morcos and Akila N. Viswanathan and Shirin A. Enger},
doi = {10.1002/mp.14802},
issn = {2473-4209},
year = {2021},
date = {2021-05-01},
journal = {Medical Physics},
volume = {48},
number = {5},
pages = {2604--2613},
abstract = {PURPOSE: The purpose of this study was to evaluate the impact of dose reporting schemes and tissue/applicator heterogeneities for 192 Ir-, 75 Se-, and 169 Yb-based MRI-guided conventional and intensity-modulated brachytherapy. METHODS AND MATERIALS: Treatment plans using a variety of dose reporting and tissue/applicator segmentation schemes were generated for a cohort (n = 10) of cervical cancer patients treated with 192 Ir-based Venezia brachytherapy. Dose calculations were performed using RapidBrachyMCTPS, a Geant4-based research Monte Carlo treatment planning system. Ultimately, five dose calculation scenarios were evaluated: (a) dose to water in water (Dw,w ); (b) Dw,w taking the applicator material into consideration (Dw,wApp ); (c) dose to water in medium (Dw,m ); (d and e) dose to medium in medium with mass densities assigned either nominally per structure (Dm,m (Nom) ) or voxel-by-voxel (Dm,m ).
RESULTS: Ignoring the plastic Venezia applicator (Dw,wApp ) overestimates Dm,m by up to 1% (average) with high energy source (192 Ir and 75 Se) and up to 2% with 169 Yb. Scoring dose to water (Dw,wApp or Dw,m ) generally overestimates dose and this effect increases with decreasing photon energy. Reporting dose other than Dm,m (or Dm,m Nom ) for 169 Yb-based conventional and intensity-modulated brachytherapy leads to a simultaneous overestimation (up to 4%) of CTVHR D90 and underestimation (up to 2%) of bladder D2cc due to a significant dip in the mass-energy absorption ratios at the depths of nearby targets and OARs. Using a nominal mass-density assignment per structure, rather than a CT-derived voxel-by-voxel assignment for MRI-guided brachytherapy, amounts to a dose error up to 1% for all radionuclides considered.
CONCLUSIONS: The effects of the considered dose reporting schemes trend correspondingly between conventional and intensity-modulated brachytherapy. In the absence of CT-derived mass densities, MRI-only-based dosimetry can adequately approximate Dm,m by assigning nominal mass densities to structures. Tissue and applicator heterogeneities do not significantly impact dosimetry for 192 Ir and 75 Se, but do for 169 Yb; dose reporting must be explicitly defined since Dw,m and Dw,w may overstate the dosimetric benefits.},
keywords = {Brachytherapy, Computer-Assisted, dynamic shield brachytherapy, Female, Humans, IMBT, Intensity modulated brachytherapy, Iridium Radioisotopes, Monte Carlo Method, MR-guided brachytherapy, Radiotherapy Dosage, Radiotherapy Planning, rotating shield brachytherapy, RSBT, Uterine Cervical Neoplasms},
pubstate = {published},
tppubtype = {article}
}
PURPOSE: The purpose of this study was to evaluate the impact of dose reporting schemes and tissue/applicator heterogeneities for 192 Ir-, 75 Se-, and 169 Yb-based MRI-guided conventional and intensity-modulated brachytherapy. METHODS AND MATERIALS: Treatment plans using a variety of dose reporting and tissue/applicator segmentation schemes were generated for a cohort (n = 10) of cervical cancer patients treated with 192 Ir-based Venezia brachytherapy. Dose calculations were performed using RapidBrachyMCTPS, a Geant4-based research Monte Carlo treatment planning system. Ultimately, five dose calculation scenarios were evaluated: (a) dose to water in water (Dw,w ); (b) Dw,w taking the applicator material into consideration (Dw,wApp ); (c) dose to water in medium (Dw,m ); (d and e) dose to medium in medium with mass densities assigned either nominally per structure (Dm,m (Nom) ) or voxel-by-voxel (Dm,m ).
RESULTS: Ignoring the plastic Venezia applicator (Dw,wApp ) overestimates Dm,m by up to 1% (average) with high energy source (192 Ir and 75 Se) and up to 2% with 169 Yb. Scoring dose to water (Dw,wApp or Dw,m ) generally overestimates dose and this effect increases with decreasing photon energy. Reporting dose other than Dm,m (or Dm,m Nom ) for 169 Yb-based conventional and intensity-modulated brachytherapy leads to a simultaneous overestimation (up to 4%) of CTVHR D90 and underestimation (up to 2%) of bladder D2cc due to a significant dip in the mass-energy absorption ratios at the depths of nearby targets and OARs. Using a nominal mass-density assignment per structure, rather than a CT-derived voxel-by-voxel assignment for MRI-guided brachytherapy, amounts to a dose error up to 1% for all radionuclides considered.
CONCLUSIONS: The effects of the considered dose reporting schemes trend correspondingly between conventional and intensity-modulated brachytherapy. In the absence of CT-derived mass densities, MRI-only-based dosimetry can adequately approximate Dm,m by assigning nominal mass densities to structures. Tissue and applicator heterogeneities do not significantly impact dosimetry for 192 Ir and 75 Se, but do for 169 Yb; dose reporting must be explicitly defined since Dw,m and Dw,w may overstate the dosimetric benefits.
RESULTS: Ignoring the plastic Venezia applicator (Dw,wApp ) overestimates Dm,m by up to 1% (average) with high energy source (192 Ir and 75 Se) and up to 2% with 169 Yb. Scoring dose to water (Dw,wApp or Dw,m ) generally overestimates dose and this effect increases with decreasing photon energy. Reporting dose other than Dm,m (or Dm,m Nom ) for 169 Yb-based conventional and intensity-modulated brachytherapy leads to a simultaneous overestimation (up to 4%) of CTVHR D90 and underestimation (up to 2%) of bladder D2cc due to a significant dip in the mass-energy absorption ratios at the depths of nearby targets and OARs. Using a nominal mass-density assignment per structure, rather than a CT-derived voxel-by-voxel assignment for MRI-guided brachytherapy, amounts to a dose error up to 1% for all radionuclides considered.
CONCLUSIONS: The effects of the considered dose reporting schemes trend correspondingly between conventional and intensity-modulated brachytherapy. In the absence of CT-derived mass densities, MRI-only-based dosimetry can adequately approximate Dm,m by assigning nominal mass densities to structures. Tissue and applicator heterogeneities do not significantly impact dosimetry for 192 Ir and 75 Se, but do for 169 Yb; dose reporting must be explicitly defined since Dw,m and Dw,w may overstate the dosimetric benefits.
Weishaupt, Luca L.; Torres, Jose; Camilleri-Broët, Sophie; Rayes, Roni F.; Spicer, Jonathan D.; Maldonado, Sabrina Côté; Enger, Shirin A.
Deep learning-based tumor segmentation on digital images of histopathology slides for microdosimetry applications Journal Article
In: arXiv:2105.01824 [physics], 2021, (arXiv: 2105.01824).
Abstract | Links | BibTeX | Tags: Physics - Medical Physics
@article{weishaupt_deep_2021,
title = {Deep learning-based tumor segmentation on digital images of histopathology slides for microdosimetry applications},
author = {Luca L. Weishaupt and Jose Torres and Sophie Camilleri-Broët and Roni F. Rayes and Jonathan D. Spicer and Sabrina Côté Maldonado and Shirin A. Enger},
url = {http://arxiv.org/abs/2105.01824},
year = {2021},
date = {2021-05-01},
urldate = {2021-09-08},
journal = {arXiv:2105.01824 [physics]},
abstract = {$textbackslashbfPurpose:$ The goal of this study was (i) to use artificial intelligence to automate the traditionally labor-intensive process of manual segmentation of tumor regions in pathology slides performed by a pathologist and (ii) to validate the use of a well-known and readily available deep learning architecture. Automation will reduce the human error involved in manual delineation, increase efficiency, and result in accurate and reproducible segmentation. This advancement will alleviate the bottleneck in the workflow in clinical and research applications due to a lack of pathologist time. Our application is patient-specific microdosimetry and radiobiological modeling, which builds on the contoured pathology slides. $textbackslashbfMethods:$ A U-Net architecture was used to segment tumor regions in pathology core biopsies of lung tissue with adenocarcinoma stained using hematoxylin and eosin. A pathologist manually contoured the tumor regions in 56 images with binary masks for training. Overlapping patch extraction with various patch sizes and image downsampling were investigated individually. Data augmentation and 8-fold cross-validation were used. $textbackslashbfResults:$ The U-Net achieved accuracy of 0.91$textbackslashpm$0.06, specificity of 0.90$textbackslashpm$0.08, sensitivity of 0.92$textbackslashpm$0.07, and precision of 0.8$textbackslashpm$0.1. The F1/DICE score was 0.85$textbackslashpm$0.07, with a segmentation time of 3.24$textbackslashpm$0.03 seconds per image, achieving a 370$textbackslashpm$3 times increased efficiency over manual segmentation. In some cases, the U-Net correctly delineated the tumor's stroma from its epithelial component in regions that were classified as tumor by the pathologist. $textbackslashbfConclusion:$ The U-Net architecture can segment images with a level of efficiency and accuracy that makes it suitable for tumor segmentation of histopathological images in fields such as radiotherapy dosimetry, specifically in the subfields of microdosimetry.},
note = {arXiv: 2105.01824},
keywords = {Physics - Medical Physics},
pubstate = {published},
tppubtype = {article}
}
$textbackslashbfPurpose:$ The goal of this study was (i) to use artificial intelligence to automate the traditionally labor-intensive process of manual segmentation of tumor regions in pathology slides performed by a pathologist and (ii) to validate the use of a well-known and readily available deep learning architecture. Automation will reduce the human error involved in manual delineation, increase efficiency, and result in accurate and reproducible segmentation. This advancement will alleviate the bottleneck in the workflow in clinical and research applications due to a lack of pathologist time. Our application is patient-specific microdosimetry and radiobiological modeling, which builds on the contoured pathology slides. $textbackslashbfMethods:$ A U-Net architecture was used to segment tumor regions in pathology core biopsies of lung tissue with adenocarcinoma stained using hematoxylin and eosin. A pathologist manually contoured the tumor regions in 56 images with binary masks for training. Overlapping patch extraction with various patch sizes and image downsampling were investigated individually. Data augmentation and 8-fold cross-validation were used. $textbackslashbfResults:$ The U-Net achieved accuracy of 0.91$textbackslashpm$0.06, specificity of 0.90$textbackslashpm$0.08, sensitivity of 0.92$textbackslashpm$0.07, and precision of 0.8$textbackslashpm$0.1. The F1/DICE score was 0.85$textbackslashpm$0.07, with a segmentation time of 3.24$textbackslashpm$0.03 seconds per image, achieving a 370$textbackslashpm$3 times increased efficiency over manual segmentation. In some cases, the U-Net correctly delineated the tumor's stroma from its epithelial component in regions that were classified as tumor by the pathologist. $textbackslashbfConclusion:$ The U-Net architecture can segment images with a level of efficiency and accuracy that makes it suitable for tumor segmentation of histopathological images in fields such as radiotherapy dosimetry, specifically in the subfields of microdosimetry.
Thibodeau-Antonacci, Alana; Vuong, Té; Bekerat, Hamed; Childress, Lilian; Enger, Shirin A.
OC-0112 development of a dynamic-shielding intensity modulated endorectal brachytherapy applicator Presentation
Radiotherapy and Oncology, 01.05.2021, ISBN: 0167-8140, 1879-0887.
Abstract | Links | BibTeX | Tags:
@misc{Thibodeau-Antonacci2021,
title = {OC-0112 development of a dynamic-shielding intensity modulated endorectal brachytherapy applicator},
author = {Alana Thibodeau-Antonacci and Té Vuong and Hamed Bekerat and Lilian Childress and Shirin A. Enger},
url = {https://www.thegreenjournal.com/article/S0167-8140(21)06316-7/fulltext},
doi = {10.1016/S0167-8140(21)06316-7},
isbn = {0167-8140, 1879-0887},
year = {2021},
date = {2021-05-01},
abstract = {www.thegreenjournal.com},
howpublished = {Radiotherapy and Oncology},
keywords = {},
pubstate = {published},
tppubtype = {presentation}
}
Zou, Yujing; Lecavalier-Barsoum, Magali; Enger, Shirin A.
Treatment outcome Prediction for gynecological cancers patients with a machine learning model using pre/post diagnostic image modalities and digital histopathology images Presentation
CRUK RadNet Manchester AI for Optimising Radiotherapy Outcomes Workshop, 10.02.2021.
@misc{Zou2021,
title = {Treatment outcome Prediction for gynecological cancers patients with a machine learning model using pre/post diagnostic image modalities and digital histopathology images},
author = {Yujing Zou and Magali Lecavalier-Barsoum and Shirin A. Enger },
year = {2021},
date = {2021-02-10},
urldate = {2021-02-10},
abstract = {Oral Presentation (1 min fire-up pitch)},
howpublished = {CRUK RadNet Manchester AI for Optimising Radiotherapy Outcomes Workshop},
keywords = {},
pubstate = {published},
tppubtype = {presentation}
}
Oral Presentation (1 min fire-up pitch)
Weishaupt, Luca L.
Fire-Up - Radiation Treatment Outcome Prediction Presentation
Fire-Up Presentation, 09.02.2021.
BibTeX | Tags:
@misc{luca_fireup,
title = {Fire-Up - Radiation Treatment Outcome Prediction},
author = {Luca L. Weishaupt},
year = {2021},
date = {2021-02-09},
urldate = {2021-02-09},
howpublished = {Fire-Up Presentation},
keywords = {},
pubstate = {published},
tppubtype = {presentation}
}
Morcos, Marc; Enger, Shirin A.
A novel minimally invasive IMBT delivery system for cervical cancer Presentation
JGH-Lady Davis Institute, 01.02.2021.
BibTeX | Tags:
@misc{Morcos2021b,
title = {A novel minimally invasive IMBT delivery system for cervical cancer},
author = {Marc Morcos and Shirin A. Enger},
year = {2021},
date = {2021-02-01},
howpublished = {JGH-Lady Davis Institute},
keywords = {},
pubstate = {published},
tppubtype = {presentation}
}
Morcos, Marc; Antaki, Majd; Viswanathan, Akila N.; Enger, Shirin A.
A novel minimally invasive dynamic-shield, intensity-modulated brachytherapy system for the treatment of cervical cancer Journal Article
In: Medical Physics, vol. 48, no. 1, pp. 71–79, 2021, ISSN: 2473-4209.
Abstract | Links | BibTeX | Tags: Brachytherapy, Computer-Assisted, Female, Humans, Image-guided cervix brachytherapy, Intensity modulated brachytherapy, Monte Carlo based dosimetry, Monte Carlo Method, MRI-guided GYN brachytherapy, Organs at Risk, Radiotherapy Dosage, Radiotherapy Planning, Uterine Cervical Neoplasms
@article{morcos_novel_2021,
title = {A novel minimally invasive dynamic-shield, intensity-modulated brachytherapy system for the treatment of cervical cancer},
author = {Marc Morcos and Majd Antaki and Akila N. Viswanathan and Shirin A. Enger},
doi = {10.1002/mp.14459},
issn = {2473-4209},
year = {2021},
date = {2021-01-01},
journal = {Medical Physics},
volume = {48},
number = {1},
pages = {71--79},
abstract = {PURPOSE: To present a novel, MRI-compatible dynamicshield intensity modulated brachytherapy (IMBT) applicator and delivery system using 192 Ir, 75 Se, and 169 Yb radioisotopes for the treatment of locally advanced cervical cancer. Needle-free IMBT is a promising technique for improving target coverage and organs at risk (OAR) sparing.
METHODS AND MATERIALS: The IMBT delivery system dynamically controls the rotation of a novel tungsten shield placed inside an MRI-compatible, 6-mm wide intrauterine tandem. Using 36 cervical cancer cases, conventional intracavitary brachytherapy (IC-BT) and intracavitary/interstitial brachytherapy (IC/IS-BT) (10Ci 192 Ir) plans were compared to IMBT (10Ci 192 Ir; 11.5Ci 75 Se; 44Ci 169 Yb). All plans were generated using the Geant4-based Monte Carlo dose calculation engine, RapidBrachyMC. Treatment plans were optimized then normalized to the same high-risk clinical target volume (HR-CTV) D90 and the D2cc for bladder, rectum, and sigmoid in the research brachytherapy planning system, RapidBrachyMCTPS. Plans were renormalized until either of the three OAR reached dose limits to calculate the maximum achievable HR-CTV D90 and D98 . RESULTS: Compared to IC-BT, IMBT with either of the three radionuclides significantly improves the HR-CTV D90 and D98 by up to 5.2% ± 0.3% (P textless 0.001) and 6.7% ± 0.5% (P textless 0.001), respectively, with the largest dosimetric enhancement when using 169 Yb followed by 75 Se and then 192 Ir. Similarly, D2cc for all OAR improved with IMBT by up to 7.7% ± 0.6% (P textless 0.001). For IC/IS-BT cases, needle-free IMBT achieved clinically acceptable plans with 169 Yb-based IMBT further improving HR-CTV D98 by 1.5% ± 0.2% (P = 0.034) and decreasing sigmoid D2cc by 1.9% ± 0.4% (P = 0.048). Delivery times for IMBT are increased by a factor of 1.7, 3.3, and 2.3 for 192 Ir, 75 Se, and 169 Yb, respectively, relative to conventional 192 Ir BT.
CONCLUSIONS: Dynamic shield IMBT provides a promising alternative to conventional IC- and IC/IS-BT techniques with significant dosimetric enhancements and even greater improvements with intermediate energy radionuclides. The ability to deliver a highly conformal, OAR-sparing dose without IS needles provides a simplified method for improving the therapeutic ratio less invasively and in a less resource intensive manner.},
keywords = {Brachytherapy, Computer-Assisted, Female, Humans, Image-guided cervix brachytherapy, Intensity modulated brachytherapy, Monte Carlo based dosimetry, Monte Carlo Method, MRI-guided GYN brachytherapy, Organs at Risk, Radiotherapy Dosage, Radiotherapy Planning, Uterine Cervical Neoplasms},
pubstate = {published},
tppubtype = {article}
}
PURPOSE: To present a novel, MRI-compatible dynamicshield intensity modulated brachytherapy (IMBT) applicator and delivery system using 192 Ir, 75 Se, and 169 Yb radioisotopes for the treatment of locally advanced cervical cancer. Needle-free IMBT is a promising technique for improving target coverage and organs at risk (OAR) sparing.
METHODS AND MATERIALS: The IMBT delivery system dynamically controls the rotation of a novel tungsten shield placed inside an MRI-compatible, 6-mm wide intrauterine tandem. Using 36 cervical cancer cases, conventional intracavitary brachytherapy (IC-BT) and intracavitary/interstitial brachytherapy (IC/IS-BT) (10Ci 192 Ir) plans were compared to IMBT (10Ci 192 Ir; 11.5Ci 75 Se; 44Ci 169 Yb). All plans were generated using the Geant4-based Monte Carlo dose calculation engine, RapidBrachyMC. Treatment plans were optimized then normalized to the same high-risk clinical target volume (HR-CTV) D90 and the D2cc for bladder, rectum, and sigmoid in the research brachytherapy planning system, RapidBrachyMCTPS. Plans were renormalized until either of the three OAR reached dose limits to calculate the maximum achievable HR-CTV D90 and D98 . RESULTS: Compared to IC-BT, IMBT with either of the three radionuclides significantly improves the HR-CTV D90 and D98 by up to 5.2% ± 0.3% (P textless 0.001) and 6.7% ± 0.5% (P textless 0.001), respectively, with the largest dosimetric enhancement when using 169 Yb followed by 75 Se and then 192 Ir. Similarly, D2cc for all OAR improved with IMBT by up to 7.7% ± 0.6% (P textless 0.001). For IC/IS-BT cases, needle-free IMBT achieved clinically acceptable plans with 169 Yb-based IMBT further improving HR-CTV D98 by 1.5% ± 0.2% (P = 0.034) and decreasing sigmoid D2cc by 1.9% ± 0.4% (P = 0.048). Delivery times for IMBT are increased by a factor of 1.7, 3.3, and 2.3 for 192 Ir, 75 Se, and 169 Yb, respectively, relative to conventional 192 Ir BT.
CONCLUSIONS: Dynamic shield IMBT provides a promising alternative to conventional IC- and IC/IS-BT techniques with significant dosimetric enhancements and even greater improvements with intermediate energy radionuclides. The ability to deliver a highly conformal, OAR-sparing dose without IS needles provides a simplified method for improving the therapeutic ratio less invasively and in a less resource intensive manner.
METHODS AND MATERIALS: The IMBT delivery system dynamically controls the rotation of a novel tungsten shield placed inside an MRI-compatible, 6-mm wide intrauterine tandem. Using 36 cervical cancer cases, conventional intracavitary brachytherapy (IC-BT) and intracavitary/interstitial brachytherapy (IC/IS-BT) (10Ci 192 Ir) plans were compared to IMBT (10Ci 192 Ir; 11.5Ci 75 Se; 44Ci 169 Yb). All plans were generated using the Geant4-based Monte Carlo dose calculation engine, RapidBrachyMC. Treatment plans were optimized then normalized to the same high-risk clinical target volume (HR-CTV) D90 and the D2cc for bladder, rectum, and sigmoid in the research brachytherapy planning system, RapidBrachyMCTPS. Plans were renormalized until either of the three OAR reached dose limits to calculate the maximum achievable HR-CTV D90 and D98 . RESULTS: Compared to IC-BT, IMBT with either of the three radionuclides significantly improves the HR-CTV D90 and D98 by up to 5.2% ± 0.3% (P textless 0.001) and 6.7% ± 0.5% (P textless 0.001), respectively, with the largest dosimetric enhancement when using 169 Yb followed by 75 Se and then 192 Ir. Similarly, D2cc for all OAR improved with IMBT by up to 7.7% ± 0.6% (P textless 0.001). For IC/IS-BT cases, needle-free IMBT achieved clinically acceptable plans with 169 Yb-based IMBT further improving HR-CTV D98 by 1.5% ± 0.2% (P = 0.034) and decreasing sigmoid D2cc by 1.9% ± 0.4% (P = 0.048). Delivery times for IMBT are increased by a factor of 1.7, 3.3, and 2.3 for 192 Ir, 75 Se, and 169 Yb, respectively, relative to conventional 192 Ir BT.
CONCLUSIONS: Dynamic shield IMBT provides a promising alternative to conventional IC- and IC/IS-BT techniques with significant dosimetric enhancements and even greater improvements with intermediate energy radionuclides. The ability to deliver a highly conformal, OAR-sparing dose without IS needles provides a simplified method for improving the therapeutic ratio less invasively and in a less resource intensive manner.
DeCunha, Joseph M.; Poole, Christopher M.; Vallières, Martin; Torres, Jose; Camilleri-Broët, Sophie; Rayes, Roni F.; Spicer, Jonathan D.; Enger, Shirin A.
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.
Abstract | Links | BibTeX | Tags: Algorithms, Cell Nucleus, Cellular dosimetry, Histopathology, Humans, Microdosimetry, Patient-specific, Radiometry
@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.
DeCunha, Joseph M.; Villegas, Fernanda; Vallières, Martin; Torres, Jose; Camilleri-Broët, Sophie; Enger, Shirin A.
Patient-specific microdosimetry: a proof of concept Journal Article
In: Physics in Medicine & Biology, 2021, ISSN: 0031-9155.
Abstract | Links | BibTeX | Tags:
@article{decunha_patient-specific_2021b,
title = {Patient-specific microdosimetry: a proof of concept},
author = {Joseph M. DeCunha and Fernanda Villegas and Martin Vallières and Jose Torres and Sophie Camilleri-Broët and Shirin A. Enger},
url = {http://iopscience.iop.org/article/10.1088/1361-6560/ac1d1e},
doi = {10.1088/1361-6560/ac1d1e},
issn = {0031-9155},
year = {2021},
date = {2021-01-01},
urldate = {2021-01-01},
journal = {Physics in Medicine & Biology},
abstract = {Microscopic energy deposition distributions from ionizing radiation are used to predict the biological effects of an irradiation and vary depending on biological target size. Ionizing radiation is thought to kill cells or inhibit cell cycling mainly by damaging DNA in the cell nucleus. The size of cells and nuclei depends on tissue type, cell cycle, and malignancy, all of which vary between patients. The aim of this study was to develop methods to perform patient-specific microdosimetry, that being, determining microdosimetric quantities in volumes that correspond to the sizes of cells and nuclei observed in a patient’s tissue. A histopathological sample extracted from a stage I lung adenocarcinoma patient was analyzed. A pouring simulation was used to generate a three-dimensional tissue model from cell and nucleus size information determined from the histopathological sample. Microdosimetric distributions including f(y) and d(y) were determined for Co-60,Ir-192,Yb-169 and I-125 in a patient-specific model containing a distribution of cell and nucleus sizes. Fixed radius models and a summation method (where f(y) from many fixed radii models are summed) were compared to the full patient-specific model to evaluate their suitability for fast determination of patient-specific microdosimetric parameters. Fixed radius models do not provide a close approximation of the full patient-specific model y ̅_f or y ̅_d for the lower energy sources investigated, Yb-169 and I-125. The higher energy sources investigated, Co-60 and Ir-192 are less sensitive to target size variation than Yb-169 and I-125. A summation method yields the most accurate approximation of the full model d(y) for all radioisotopes investigated. A summation method allows for the computation of patient-specific microdosimetric distributions with the computing power of a personal computer. With appropriate biological inputs the microdosimetric distributions computed using these methods can yield a patient-specific relative biological effectiveness as part of a multiscale treatment planning approach.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Microscopic energy deposition distributions from ionizing radiation are used to predict the biological effects of an irradiation and vary depending on biological target size. Ionizing radiation is thought to kill cells or inhibit cell cycling mainly by damaging DNA in the cell nucleus. The size of cells and nuclei depends on tissue type, cell cycle, and malignancy, all of which vary between patients. The aim of this study was to develop methods to perform patient-specific microdosimetry, that being, determining microdosimetric quantities in volumes that correspond to the sizes of cells and nuclei observed in a patient’s tissue. A histopathological sample extracted from a stage I lung adenocarcinoma patient was analyzed. A pouring simulation was used to generate a three-dimensional tissue model from cell and nucleus size information determined from the histopathological sample. Microdosimetric distributions including f(y) and d(y) were determined for Co-60,Ir-192,Yb-169 and I-125 in a patient-specific model containing a distribution of cell and nucleus sizes. Fixed radius models and a summation method (where f(y) from many fixed radii models are summed) were compared to the full patient-specific model to evaluate their suitability for fast determination of patient-specific microdosimetric parameters. Fixed radius models do not provide a close approximation of the full patient-specific model y ̅_f or y ̅_d for the lower energy sources investigated, Yb-169 and I-125. The higher energy sources investigated, Co-60 and Ir-192 are less sensitive to target size variation than Yb-169 and I-125. A summation method yields the most accurate approximation of the full model d(y) for all radioisotopes investigated. A summation method allows for the computation of patient-specific microdosimetric distributions with the computing power of a personal computer. With appropriate biological inputs the microdosimetric distributions computed using these methods can yield a patient-specific relative biological effectiveness as part of a multiscale treatment planning approach.
Deufel, Christopher; Weishaupt, Luca L.; Sayed, Hisham Kamal; Choo, Chunhee; Stish, Bradley
Deep learning for automated applicator reconstruction in high-dose-rate prostate brachytherapy Journal Article
In: World Congress of Brachytherapy 2021, 2021, (Type: Journal Article).
@article{deufel_deep_2021,
title = {Deep learning for automated applicator reconstruction in high-dose-rate prostate brachytherapy},
author = {Christopher Deufel and Luca L. Weishaupt and Hisham Kamal Sayed and Chunhee Choo and Bradley Stish},
url = {https://www.estro.org/Congresses/WCB-2021/811/poster-physics/3229/deeplearningforautomatedapplicatorreconstructionin},
year = {2021},
date = {2021-01-01},
journal = {World Congress of Brachytherapy 2021},
note = {Type: Journal Article},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Weishaupt, Luca L.; Sayed, Hisham Kamal; Mao, Ximeng; Choo, Chunhee; Stish, Bradley; Enger, Shirin A.; Deufel, Christopher
Approaching automated applicator digitization from a new angle: using sagittal images to improve deep learning accuracy and robustness in high-dose-rate prostate brachytherapy Journal Article
In: 2021 ABS Annual Meeting, 2021, (Type: Journal Article).
BibTeX | Tags:
@article{weishaupt_approaching_2021-1,
title = {Approaching automated applicator digitization from a new angle: using sagittal images to improve deep learning accuracy and robustness in high-dose-rate prostate brachytherapy},
author = {Luca L. Weishaupt and Hisham Kamal Sayed and Ximeng Mao and Chunhee Choo and Bradley Stish and Shirin A. Enger and Christopher Deufel},
year = {2021},
date = {2021-01-01},
journal = {2021 ABS Annual Meeting},
note = {Type: Journal Article},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Morcos, Marc; Viswanathan, Akila N.; Enger, Shirin A.
In: Medical Physics, vol. 48, no. 5, pp. 2604–2613, 2021, ISSN: 2473-4209, (_eprint: https://aapm.onlinelibrary.wiley.com/doi/pdf/10.1002/mp.14802).
Abstract | Links | BibTeX | Tags: dynamic shield brachytherapy, IMBT, Intensity modulated brachytherapy, MR-guided brachytherapy, rotating shield brachytherapy, RSBT
@article{morcos_impact_2021b,
title = {On the impact of absorbed dose specification, tissue heterogeneities, and applicator heterogeneities on Monte Carlo-based dosimetry of Ir-192, Se-75, and Yb-169 in conventional and intensity-modulated brachytherapy for the treatment of cervical cancer},
author = {Marc Morcos and Akila N. Viswanathan and Shirin A. Enger},
url = {https://aapm.onlinelibrary.wiley.com/doi/abs/10.1002/mp.14802},
doi = {10.1002/mp.14802},
issn = {2473-4209},
year = {2021},
date = {2021-01-01},
urldate = {2021-09-08},
journal = {Medical Physics},
volume = {48},
number = {5},
pages = {2604--2613},
abstract = {Purpose The purpose of this study was to evaluate the impact of dose reporting schemes and tissue/applicator heterogeneities for 192Ir-, 75Se-, and 169Yb-based MRI-guided conventional and intensity-modulated brachytherapy. Methods and Materials Treatment plans using a variety of dose reporting and tissue/applicator segmentation schemes were generated for a cohort (n = 10) of cervical cancer patients treated with 192Ir-based Venezia brachytherapy. Dose calculations were performed using RapidBrachyMCTPS, a Geant4-based research Monte Carlo treatment planning system. Ultimately, five dose calculation scenarios were evaluated: (a) dose to water in water (Dw,w); (b) Dw,w taking the applicator material into consideration (Dw,wApp); (c) dose to water in medium (Dw,m); (d and e) dose to medium in medium with mass densities assigned either nominally per structure (Dm,m (Nom)) or voxel-by-voxel (Dm,m). Results Ignoring the plastic Venezia applicator (Dw,wApp) overestimates Dm,m by up to 1% (average) with high energy source (192Ir and 75Se) and up to 2% with 169Yb. Scoring dose to water (Dw,wApp or Dw,m) generally overestimates dose and this effect increases with decreasing photon energy. Reporting dose other than Dm,m (or Dm,m Nom) for 169Yb-based conventional and intensity-modulated brachytherapy leads to a simultaneous overestimation (up to 4%) of CTVHR D90 and underestimation (up to 2%) of bladder D2cc due to a significant dip in the mass-energy absorption ratios at the depths of nearby targets and OARs. Using a nominal mass-density assignment per structure, rather than a CT-derived voxel-by-voxel assignment for MRI-guided brachytherapy, amounts to a dose error up to 1% for all radionuclides considered. Conclusions The effects of the considered dose reporting schemes trend correspondingly between conventional and intensity-modulated brachytherapy. In the absence of CT-derived mass densities, MRI-only-based dosimetry can adequately approximate Dm,m by assigning nominal mass densities to structures. Tissue and applicator heterogeneities do not significantly impact dosimetry for 192Ir and 75Se, but do for 169Yb; dose reporting must be explicitly defined since Dw,m and Dw,w may overstate the dosimetric benefits.},
note = {_eprint: https://aapm.onlinelibrary.wiley.com/doi/pdf/10.1002/mp.14802},
keywords = {dynamic shield brachytherapy, IMBT, Intensity modulated brachytherapy, MR-guided brachytherapy, rotating shield brachytherapy, RSBT},
pubstate = {published},
tppubtype = {article}
}
Purpose The purpose of this study was to evaluate the impact of dose reporting schemes and tissue/applicator heterogeneities for 192Ir-, 75Se-, and 169Yb-based MRI-guided conventional and intensity-modulated brachytherapy. Methods and Materials Treatment plans using a variety of dose reporting and tissue/applicator segmentation schemes were generated for a cohort (n = 10) of cervical cancer patients treated with 192Ir-based Venezia brachytherapy. Dose calculations were performed using RapidBrachyMCTPS, a Geant4-based research Monte Carlo treatment planning system. Ultimately, five dose calculation scenarios were evaluated: (a) dose to water in water (Dw,w); (b) Dw,w taking the applicator material into consideration (Dw,wApp); (c) dose to water in medium (Dw,m); (d and e) dose to medium in medium with mass densities assigned either nominally per structure (Dm,m (Nom)) or voxel-by-voxel (Dm,m). Results Ignoring the plastic Venezia applicator (Dw,wApp) overestimates Dm,m by up to 1% (average) with high energy source (192Ir and 75Se) and up to 2% with 169Yb. Scoring dose to water (Dw,wApp or Dw,m) generally overestimates dose and this effect increases with decreasing photon energy. Reporting dose other than Dm,m (or Dm,m Nom) for 169Yb-based conventional and intensity-modulated brachytherapy leads to a simultaneous overestimation (up to 4%) of CTVHR D90 and underestimation (up to 2%) of bladder D2cc due to a significant dip in the mass-energy absorption ratios at the depths of nearby targets and OARs. Using a nominal mass-density assignment per structure, rather than a CT-derived voxel-by-voxel assignment for MRI-guided brachytherapy, amounts to a dose error up to 1% for all radionuclides considered. Conclusions The effects of the considered dose reporting schemes trend correspondingly between conventional and intensity-modulated brachytherapy. In the absence of CT-derived mass densities, MRI-only-based dosimetry can adequately approximate Dm,m by assigning nominal mass densities to structures. Tissue and applicator heterogeneities do not significantly impact dosimetry for 192Ir and 75Se, but do for 169Yb; dose reporting must be explicitly defined since Dw,m and Dw,w may overstate the dosimetric benefits.
Morcos, Marc; Antaki, Majd; Viswanathan, Akila N.; Enger, Shirin A.
ESTRO Newsletter, 2021.
@misc{nokey,
title = {A novel, minimally invasive, dynamic‐shield, intensity‐modulated brachytherapy system for the treatment of cervical cancer. Editors’ pick.},
author = {Marc Morcos and Majd Antaki and Akila N. Viswanathan and Shirin A. Enger},
url = {https://www.estro.org/About/Newsroom/Newsletter/Brachytheraphy/A-novel,-minimally-invasive,-dynamic%E2%80%90shield,-inten },
year = {2021},
date = {2021-01-01},
howpublished = {ESTRO Newsletter},
keywords = {award},
pubstate = {published},
tppubtype = {misc}
}
Morcos, Marc; Enger, Shirin A.
MR-guided intensity modulated brachytherapy for gynecologic cancers Presentation
McGill FMT, 01.01.2021.
BibTeX | Tags: Image-guided cervix brachytherapy, Intensity modulated brachytherapy, Monte Carlo based dosimetry, MRI-guided GYN brachytherapy
@misc{Morcos2021,
title = {MR-guided intensity modulated brachytherapy for gynecologic cancers},
author = {Marc Morcos and Shirin A. Enger},
year = {2021},
date = {2021-01-01},
howpublished = {McGill FMT},
keywords = {Image-guided cervix brachytherapy, Intensity modulated brachytherapy, Monte Carlo based dosimetry, MRI-guided GYN brachytherapy},
pubstate = {published},
tppubtype = {presentation}
}
2020
Antaki, Majd; Deufel, Christopher L; Enger, Shirin A.
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.
Abstract | Links | BibTeX | Tags: Algorithms, Brachytherapy, Computer-Assisted, Humans, Linear Models, Male, Monte Carlo Method, Prostatic Neoplasms, Radiation Dosage, Radiotherapy Dosage, Radiotherapy Planning, Software, Time Factors
@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.
Bui, Alaina; Childress, Lilian; Sankey, Jack; Enger, Shirin A.
Developing a hydrated electron dosimeter and determining the G-value of hydrated electrons Presentation
Association Québécoise des Physicien(ne)s Médicaux Cliniques, 05.11.2020.
BibTeX | Tags:
@misc{Bui2020,
title = {Developing a hydrated electron dosimeter and determining the G-value of hydrated electrons},
author = {Alaina Bui and Lilian Childress and Jack Sankey and Shirin A. Enger},
year = {2020},
date = {2020-11-05},
howpublished = {Association Québécoise des Physicien(ne)s Médicaux Cliniques},
keywords = {},
pubstate = {published},
tppubtype = {presentation}
}
Famulari, Gabriel; Enger, Shirin A.
La curiethérapie avec modulation d’intensité par blindage dynamique pour le cancer de la prostate Presentation
Association Québécoise des Physiciens Médicaux Cliniques (AQPMC) Annual Meeting in QC, 02.11.2020.
BibTeX | Tags:
@misc{Famulari2020b,
title = {La curiethérapie avec modulation d’intensité par blindage dynamique pour le cancer de la prostate},
author = {Gabriel Famulari and Shirin A. Enger},
year = {2020},
date = {2020-11-02},
howpublished = {Association Québécoise des Physiciens Médicaux Cliniques (AQPMC) Annual Meeting in QC},
keywords = {},
pubstate = {published},
tppubtype = {presentation}
}
Mao, Ximeng; Pineau, Joelle; Keyes, Roy; Enger, Shirin A.
RapidBrachyDL: Rapid Radiation Dose Calculations in Brachytherapy Via Deep Learning Journal Article
In: International Journal of Radiation Oncology, Biology, Physics, vol. 108, no. 3, pp. 802–812, 2020, ISSN: 1879-355X.
Abstract | Links | BibTeX | Tags: Brachytherapy, Colon, Computer, Computer-Assisted, Deep Learning, Female, Humans, Iridium Radioisotopes, Male, Monte Carlo Method, Neural Networks, Organs at Risk, Prostate, Prostatic Neoplasms, Radiotherapy Dosage, Radiotherapy Planning, Rectum, Retrospective Studies, Sigmoid, Urinary Bladder, Uterine Cervical Neoplasms
@article{mao_rapidbrachydl_2020,
title = {RapidBrachyDL: Rapid Radiation Dose Calculations in Brachytherapy Via Deep Learning},
author = {Ximeng Mao and Joelle Pineau and Roy Keyes and Shirin A. Enger},
doi = {10.1016/j.ijrobp.2020.04.045},
issn = {1879-355X},
year = {2020},
date = {2020-11-01},
journal = {International Journal of Radiation Oncology, Biology, Physics},
volume = {108},
number = {3},
pages = {802--812},
abstract = {PURPOSE: Detailed and accurate absorbed dose calculations from radiation interactions with the human body can be obtained with the Monte Carlo (MC) method. However, the MC method can be slow for use in the time-sensitive clinical workflow. The aim of this study was to provide a solution to the accuracy-time trade-off for 192Ir-based high-dose-rate brachytherapy by using deep learning.
METHODS AND MATERIALS: RapidBrachyDL, a 3-dimensional deep convolutional neural network (CNN) model, is proposed to predict dose distributions calculated with the MC method given a patient's computed tomography images, contours of clinical target volume (CTV) and organs at risk, and treatment plan. Sixty-one patients with prostate cancer and 10 patients with cervical cancer were included in this study, with data from 47 patients with prostate cancer being used to train the model.
RESULTS: Compared with ground truth MC simulations, the predicted dose distributions by RapidBrachyDL showed a consistent shape in the dose-volume histograms (DVHs); comparable DVH dosimetric indices including 0.73% difference for prostate CTV D90, 1.1% for rectum D2cc, 1.45% for urethra D0.1cc, and 1.05% for bladder D2cc; and substantially smaller prediction time, acceleration by a factor of 300. RapidBrachyDL also demonstrated good generalization to cervical data with 1.73%, 2.46%, 1.68%, and 1.74% difference for CTV D90, rectum D2cc, sigmoid D2cc, and bladder D2cc, respectively, which was unseen during the training.
CONCLUSION: Deep CNN-based dose estimation is a promising method for patient-specific brachytherapy dosimetry. Desired radiation quantities can be obtained with accuracies arbitrarily close to those of the source MC algorithm, but with much faster computation times. The idea behind deep CNN-based dose estimation can be safely extended to other radiation sources and tumor sites by following a similar training process.},
keywords = {Brachytherapy, Colon, Computer, Computer-Assisted, Deep Learning, Female, Humans, Iridium Radioisotopes, Male, Monte Carlo Method, Neural Networks, Organs at Risk, Prostate, Prostatic Neoplasms, Radiotherapy Dosage, Radiotherapy Planning, Rectum, Retrospective Studies, Sigmoid, Urinary Bladder, Uterine Cervical Neoplasms},
pubstate = {published},
tppubtype = {article}
}
PURPOSE: Detailed and accurate absorbed dose calculations from radiation interactions with the human body can be obtained with the Monte Carlo (MC) method. However, the MC method can be slow for use in the time-sensitive clinical workflow. The aim of this study was to provide a solution to the accuracy-time trade-off for 192Ir-based high-dose-rate brachytherapy by using deep learning.
METHODS AND MATERIALS: RapidBrachyDL, a 3-dimensional deep convolutional neural network (CNN) model, is proposed to predict dose distributions calculated with the MC method given a patient's computed tomography images, contours of clinical target volume (CTV) and organs at risk, and treatment plan. Sixty-one patients with prostate cancer and 10 patients with cervical cancer were included in this study, with data from 47 patients with prostate cancer being used to train the model.
RESULTS: Compared with ground truth MC simulations, the predicted dose distributions by RapidBrachyDL showed a consistent shape in the dose-volume histograms (DVHs); comparable DVH dosimetric indices including 0.73% difference for prostate CTV D90, 1.1% for rectum D2cc, 1.45% for urethra D0.1cc, and 1.05% for bladder D2cc; and substantially smaller prediction time, acceleration by a factor of 300. RapidBrachyDL also demonstrated good generalization to cervical data with 1.73%, 2.46%, 1.68%, and 1.74% difference for CTV D90, rectum D2cc, sigmoid D2cc, and bladder D2cc, respectively, which was unseen during the training.
CONCLUSION: Deep CNN-based dose estimation is a promising method for patient-specific brachytherapy dosimetry. Desired radiation quantities can be obtained with accuracies arbitrarily close to those of the source MC algorithm, but with much faster computation times. The idea behind deep CNN-based dose estimation can be safely extended to other radiation sources and tumor sites by following a similar training process.
METHODS AND MATERIALS: RapidBrachyDL, a 3-dimensional deep convolutional neural network (CNN) model, is proposed to predict dose distributions calculated with the MC method given a patient's computed tomography images, contours of clinical target volume (CTV) and organs at risk, and treatment plan. Sixty-one patients with prostate cancer and 10 patients with cervical cancer were included in this study, with data from 47 patients with prostate cancer being used to train the model.
RESULTS: Compared with ground truth MC simulations, the predicted dose distributions by RapidBrachyDL showed a consistent shape in the dose-volume histograms (DVHs); comparable DVH dosimetric indices including 0.73% difference for prostate CTV D90, 1.1% for rectum D2cc, 1.45% for urethra D0.1cc, and 1.05% for bladder D2cc; and substantially smaller prediction time, acceleration by a factor of 300. RapidBrachyDL also demonstrated good generalization to cervical data with 1.73%, 2.46%, 1.68%, and 1.74% difference for CTV D90, rectum D2cc, sigmoid D2cc, and bladder D2cc, respectively, which was unseen during the training.
CONCLUSION: Deep CNN-based dose estimation is a promising method for patient-specific brachytherapy dosimetry. Desired radiation quantities can be obtained with accuracies arbitrarily close to those of the source MC algorithm, but with much faster computation times. The idea behind deep CNN-based dose estimation can be safely extended to other radiation sources and tumor sites by following a similar training process.
Turgeon, Vincent; Morcos, Marc; Antaki, Majd; Enger, Shirin A.
Impact of choices in dosimetric calculation method for high dose rate brachytherapy of breast cancer Presentation
Radiotherapy and Oncology, 01.11.2020, ISSN: 0167-8140, 1879-0887.
Abstract | Links | BibTeX | Tags:
@misc{Turgeon2020,
title = {Impact of choices in dosimetric calculation method for high dose rate brachytherapy of breast cancer},
author = {Vincent Turgeon and Marc Morcos and Majd Antaki and Shirin A. Enger},
url = {https://www.thegreenjournal.com/article/S0167-8140(21)01974-5/fulltext},
doi = {10.1016/S0167-8140(21)01974-5},
issn = {0167-8140, 1879-0887},
year = {2020},
date = {2020-11-01},
abstract = {www.thegreenjournal.com},
howpublished = {Radiotherapy and Oncology},
keywords = {},
pubstate = {published},
tppubtype = {presentation}
}
Famulari, Gabriel; Rosales, Haydee M. Linares; Dupere, Justine; Medich, David C.; Beaulieu, Luc; Enger, Shirin A.
In: Medical Physics, vol. 47, no. 9, pp. 4563–4573, 2020, ISSN: 2473-4209.
Abstract | Links | BibTeX | Tags: Brachytherapy, Geant4, IMBT, Monte Carlo Method, mPSD, Plastics, Radiometry, Radiotherapy Dosage, shielded applicator, TG-186, TG-43, Yb-169
@article{famulari_monte_2020,
title = {Monte Carlo dosimetric characterization of a new high dose rate 169 Yb brachytherapy source and independent verification using a multipoint plastic scintillator detector},
author = {Gabriel Famulari and Haydee M. Linares Rosales and Justine Dupere and David C. Medich and Luc Beaulieu and Shirin A. Enger},
doi = {10.1002/mp.14336},
issn = {2473-4209},
year = {2020},
date = {2020-09-01},
journal = {Medical Physics},
volume = {47},
number = {9},
pages = {4563--4573},
abstract = {PURPOSE: A prototype 169 Yb source was developed in combination with a dynamic rotating platinum shield system (AIM-Brachy) to deliver intensity modulated brachytherapy (IMBT). The purpose of this study was to evaluate the dosimetric characteristics of the bare/shielded 169 Yb source using Monte Carlo (MC) simulations and perform an independent dose verification using a dosimetry platform based on a multipoint plastic scintillator detector (mPSD).
METHODS: The TG-43U1 dosimetric parameters were calculated for the source model using RapidBrachyMCTPS. Real-time dose rate measurements were performed in a water tank for both the bare/shielded source using a custom remote afterloader. For each dwell position, the dose rate was independently measured by the three scintillators (BCF-10, BCF-12, and BCF-60). For the bare source, dose rate was measured at distances up to 3 cm away from the source over a range of 7 cm along the catheter. For the shielded source, measurements were performed with the mPSD placed at 1 cm from the source at four different azimuthal angles ( 0 ∘ , 9 0 ∘ , 18 0 ∘ , and 27 0 ∘ ).
RESULTS: The dosimetric parameters were tabulated for the source model. For the bare source, differences between measured and calculated along-away dose rates were generally below 5-10%. Along the transverse axis, deviations were, on average (range), 3.3% (0.6-6.2%) for BCF-10, 1.7% (0.9-2.9%) for BCF-12, and 2.2% (0.3-4.4%) for BCF-60. The maximum dose rate reduction due to shielding at a radial distance of 1 cm was 88.8 ± 1.2%, compared to 83.5 ± 0.5% as calculated by MC.
CONCLUSIONS: The dose distribution for the bare/shielded 169 Yb source was independently verified using mPSD with good agreement in regions close to the source. The 169 Yb source coupled with the partial-shielding system is an effective technique to deliver IMBT.},
keywords = {Brachytherapy, Geant4, IMBT, Monte Carlo Method, mPSD, Plastics, Radiometry, Radiotherapy Dosage, shielded applicator, TG-186, TG-43, Yb-169},
pubstate = {published},
tppubtype = {article}
}
PURPOSE: A prototype 169 Yb source was developed in combination with a dynamic rotating platinum shield system (AIM-Brachy) to deliver intensity modulated brachytherapy (IMBT). The purpose of this study was to evaluate the dosimetric characteristics of the bare/shielded 169 Yb source using Monte Carlo (MC) simulations and perform an independent dose verification using a dosimetry platform based on a multipoint plastic scintillator detector (mPSD).
METHODS: The TG-43U1 dosimetric parameters were calculated for the source model using RapidBrachyMCTPS. Real-time dose rate measurements were performed in a water tank for both the bare/shielded source using a custom remote afterloader. For each dwell position, the dose rate was independently measured by the three scintillators (BCF-10, BCF-12, and BCF-60). For the bare source, dose rate was measured at distances up to 3 cm away from the source over a range of 7 cm along the catheter. For the shielded source, measurements were performed with the mPSD placed at 1 cm from the source at four different azimuthal angles ( 0 ∘ , 9 0 ∘ , 18 0 ∘ , and 27 0 ∘ ).
RESULTS: The dosimetric parameters were tabulated for the source model. For the bare source, differences between measured and calculated along-away dose rates were generally below 5-10%. Along the transverse axis, deviations were, on average (range), 3.3% (0.6-6.2%) for BCF-10, 1.7% (0.9-2.9%) for BCF-12, and 2.2% (0.3-4.4%) for BCF-60. The maximum dose rate reduction due to shielding at a radial distance of 1 cm was 88.8 ± 1.2%, compared to 83.5 ± 0.5% as calculated by MC.
CONCLUSIONS: The dose distribution for the bare/shielded 169 Yb source was independently verified using mPSD with good agreement in regions close to the source. The 169 Yb source coupled with the partial-shielding system is an effective technique to deliver IMBT.
METHODS: The TG-43U1 dosimetric parameters were calculated for the source model using RapidBrachyMCTPS. Real-time dose rate measurements were performed in a water tank for both the bare/shielded source using a custom remote afterloader. For each dwell position, the dose rate was independently measured by the three scintillators (BCF-10, BCF-12, and BCF-60). For the bare source, dose rate was measured at distances up to 3 cm away from the source over a range of 7 cm along the catheter. For the shielded source, measurements were performed with the mPSD placed at 1 cm from the source at four different azimuthal angles ( 0 ∘ , 9 0 ∘ , 18 0 ∘ , and 27 0 ∘ ).
RESULTS: The dosimetric parameters were tabulated for the source model. For the bare source, differences between measured and calculated along-away dose rates were generally below 5-10%. Along the transverse axis, deviations were, on average (range), 3.3% (0.6-6.2%) for BCF-10, 1.7% (0.9-2.9%) for BCF-12, and 2.2% (0.3-4.4%) for BCF-60. The maximum dose rate reduction due to shielding at a radial distance of 1 cm was 88.8 ± 1.2%, compared to 83.5 ± 0.5% as calculated by MC.
CONCLUSIONS: The dose distribution for the bare/shielded 169 Yb source was independently verified using mPSD with good agreement in regions close to the source. The 169 Yb source coupled with the partial-shielding system is an effective technique to deliver IMBT.
Zou, Yujing
Graduate Excellence Fellowship award
2020.
BibTeX | Tags:
@award{nokey,
title = {Graduate Excellence Fellowship},
author = {Yujing Zou},
year = {2020},
date = {2020-09-01},
urldate = {2020-09-01},
organization = {McGill Medical Physics Unit},
keywords = {},
pubstate = {published},
tppubtype = {award}
}
Carroll, Liam; Croteau, Etienne; Kertzscher, Gustavo; Sarrhini, Otman; Turgeon, Vincent; Lecomte, Roger; Enger, Shirin A.
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.
Abstract | Links | BibTeX | Tags: Algorithms, Arterial input function, Arteries, Dynamic PET, Electrons, Humans, Imaging, Non-invasive detector development, Phantoms, Positron-Emission Tomography, Scintillation
@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.
Behmand, Behnaz; Kamio, Yuji; Evans, Michael D. C.; Enger, Shirin A.
Correlation Between Radiation-Induced Foci and Tumor Nuclei Size Distribution Presentation
AAPM | COMP Virtual Meeting, 12.07.2020.
BibTeX | Tags:
@misc{Behmand2020,
title = {Correlation Between Radiation-Induced Foci and Tumor Nuclei Size Distribution},
author = {Behnaz Behmand and Yuji Kamio and Michael D. C. Evans and Shirin A. Enger},
year = {2020},
date = {2020-07-12},
howpublished = {AAPM | COMP Virtual Meeting},
keywords = {},
pubstate = {published},
tppubtype = {presentation}
}
Famulari, Gabriel; Enger, Shirin A.
AIM-Brachy: a novel intensity modulated brachytherapy (IMBT) delivery system for prostate cancer. Winner of the 2019 Jean Pouliot Prize for best paper published in 2019 awarded by Association Québécoise des Physicien(ne) Médicaux Cliniques. award
2020.
@award{Famulari2020,
title = {AIM-Brachy: a novel intensity modulated brachytherapy (IMBT) delivery system for prostate cancer. Winner of the 2019 Jean Pouliot Prize for best paper published in 2019 awarded by Association Québécoise des Physicien(ne) Médicaux Cliniques.},
author = {Gabriel Famulari and Shirin A. Enger},
year = {2020},
date = {2020-07-01},
urldate = {2020-07-01},
organization = {Association Québécoise des Physicien(ne) Médicaux Cliniques},
howpublished = {Med. Phys., 47(3):859-868 (2020)},
keywords = {award},
pubstate = {published},
tppubtype = {award}
}
Carroll, Liam
First prize for best presentation at the congrès annuel de l'AQPMC award
2020.
Abstract | BibTeX | Tags: award
@award{Carroll2020b,
title = {First prize for best presentation at the congrès annuel de l'AQPMC},
author = {Liam Carroll},
year = {2020},
date = {2020-07-01},
urldate = {2020-07-01},
organization = {Congrès Annuel de l'AQPMC},
abstract = {Nous tenons particulièrement à féliciter Liam Carroll, étudiant à McGill Medical Physics qui a remporté le prix de la meilleure présentation.},
keywords = {award},
pubstate = {published},
tppubtype = {award}
}
Nous tenons particulièrement à féliciter Liam Carroll, étudiant à McGill Medical Physics qui a remporté le prix de la meilleure présentation.
Famulari, Gabriel; Enger, Shirin A.
Monte Carlo dosimetry of a custom-made 169Yb source for intensity modulated brachytherapy Presentation
MCMA, 20.06.2020.
BibTeX | Tags:
@misc{Famulari2020c,
title = {Monte Carlo dosimetry of a custom-made 169Yb source for intensity modulated brachytherapy},
author = {Gabriel Famulari and Shirin A. Enger},
year = {2020},
date = {2020-06-20},
howpublished = {MCMA},
keywords = {},
pubstate = {published},
tppubtype = {presentation}
}
Morcos, Marc; Enger, Shirin A.
Monte Carlo Dosimetry Study of Novel Rotating MRI-Compatible Shielded Tandems for Intensity Modulated Cervix Brachytherapy Presentation
MCMA, 20.06.2020.
BibTeX | Tags:
@misc{Morcos2020,
title = {Monte Carlo Dosimetry Study of Novel Rotating MRI-Compatible Shielded Tandems for Intensity Modulated Cervix Brachytherapy},
author = {Marc Morcos and Shirin A. Enger},
year = {2020},
date = {2020-06-20},
howpublished = {MCMA},
keywords = {},
pubstate = {published},
tppubtype = {presentation}
}
Weishaupt, Luca L.; Sayed, Hisham Kamal; Mao, Ximeng; Choo, Chunhee; Stish, Bradley; Enger, Shirin A.; Deufel, Christopher
12.06.2020, (Type: Journal Article).
@misc{weishaupt_approaching_2021,
title = {Approaching automated applicator digitization from a new angle - Using sagittal images to improve deep learning accuracy and robustness in high-dose-rate prostate brachytherapy},
author = {Luca L. Weishaupt and Hisham Kamal Sayed and Ximeng Mao and Chunhee Choo and Bradley Stish and Shirin A. Enger and Christopher Deufel},
url = {https://www.postersessiononline.eu/173580348_eu/congresos/WCB2021/aula/preposter_542171716_3.png},
year = {2020},
date = {2020-06-12},
urldate = {2021-01-01},
journal = {ESTRO 2021},
note = {Type: Journal Article},
keywords = {},
pubstate = {published},
tppubtype = {presentation}
}
Weishaupt, Luca L.
Math And Physics Class Of 1965 Prize award
2020.
Abstract | BibTeX | Tags: award
@award{Weishaupt2020,
title = {Math And Physics Class Of 1965 Prize},
author = {Luca L. Weishaupt},
year = {2020},
date = {2020-06-01},
urldate = {2020-06-01},
organization = {McGill University},
abstract = {Luca received the award for his academic excellence and research activities in Medical Physics. The prize was established in 2016 by the Math and Physics Class of 1965 and is awarded by McGill Faculty of Science.
Luca is an international student from Germany that has been conducting research activities in my lab for 3 years, since his first month at McGill University. He is an active researcher as an undergraduate student. },
keywords = {award},
pubstate = {published},
tppubtype = {award}
}
Luca received the award for his academic excellence and research activities in Medical Physics. The prize was established in 2016 by the Math and Physics Class of 1965 and is awarded by McGill Faculty of Science.
Luca is an international student from Germany that has been conducting research activities in my lab for 3 years, since his first month at McGill University. He is an active researcher as an undergraduate student.
Luca is an international student from Germany that has been conducting research activities in my lab for 3 years, since his first month at McGill University. He is an active researcher as an undergraduate student.
Famulari, Gabriel; Alfieri, Joanne; Duclos, Marie; Vuong, Té; Enger, Shirin A.
Can intermediate-energy sources lead to elevated bone doses for prostate and head & neck high-dose-rate brachytherapy? Journal Article
In: Brachytherapy, vol. 19, no. 2, pp. 255–263, 2020, ISSN: 1873-1449.
Abstract | Links | BibTeX | Tags: Bone and Bones, Brachytherapy, Cobalt Radioisotopes, Computer Simulation, Computer-Assisted, Dose calculation, Gadolinium, Humans, Intermediate-energy source, Iridium Radioisotopes, Male, Monte Carlo, Prostatic Neoplasms, Radiation Dosage, Radioisotopes, Radiotherapy Dosage, Radiotherapy Planning, Selenium Radioisotopes, Tissue composition, Tongue Neoplasms, Ytterbium
@article{famulari_can_2020,
title = {Can intermediate-energy sources lead to elevated bone doses for prostate and head & neck high-dose-rate brachytherapy?},
author = {Gabriel Famulari and Joanne Alfieri and Marie Duclos and Té Vuong and Shirin A. Enger},
doi = {10.1016/j.brachy.2019.12.004},
issn = {1873-1449},
year = {2020},
date = {2020-04-01},
journal = {Brachytherapy},
volume = {19},
number = {2},
pages = {255--263},
abstract = {PURPOSE: Several radionuclides with high (60Co, 75Se) and intermediate (169Yb, 153Gd) energies have been investigated as alternatives to 192Ir for high-dose-rate brachytherapy. The purpose of this study was to evaluate the impact of tissue heterogeneities for these five high- to intermediate-energy sources in prostate and head & neck brachytherapy. METHODS AND MATERIALS: Treatment plans were generated for a cohort of prostate (n = 10) and oral tongue (n = 10) patients. Dose calculations were performed using RapidBrachyMCTPS, an in-house Geant4-based Monte Carlo treatment planning system. Treatment plans were simulated using 60Co, 192Ir, 75Se, 169Yb, and 153Gd as the active core of the microSelectron v2 source. Two dose calculation scenarios were presented: (1) dose to water in water (Dw,w), and (2) dose to medium in medium (Dm,m).
RESULTS: Dw,w overestimates planning target volume coverage compared with Dm,m, regardless of photon energy. The average planning target volume D90 reduction was ∼1% for high-energy sources, whereas larger differences were observed for intermediate-energy sources (1%-2% for prostate and 4%-7% for oral tongue). Dose differences were not clinically relevant (textless5%) for soft tissues in general. Going from Dw,w to Dm,m, bone doses were increased two- to three-fold for 169Yb and four- to five-fold for 153Gd, whereas the ratio was close to ∼1 for high-energy sources.
CONCLUSIONS: Dw,w underestimates the dose to bones and, to a lesser extent, overestimates the dose to soft tissues for radionuclides with average energies lower than 192Ir. Further studies regarding bone toxicities are needed before intermediate-energy sources can be adopted in cases where bones are in close vicinity to the tumor.},
keywords = {Bone and Bones, Brachytherapy, Cobalt Radioisotopes, Computer Simulation, Computer-Assisted, Dose calculation, Gadolinium, Humans, Intermediate-energy source, Iridium Radioisotopes, Male, Monte Carlo, Prostatic Neoplasms, Radiation Dosage, Radioisotopes, Radiotherapy Dosage, Radiotherapy Planning, Selenium Radioisotopes, Tissue composition, Tongue Neoplasms, Ytterbium},
pubstate = {published},
tppubtype = {article}
}
PURPOSE: Several radionuclides with high (60Co, 75Se) and intermediate (169Yb, 153Gd) energies have been investigated as alternatives to 192Ir for high-dose-rate brachytherapy. The purpose of this study was to evaluate the impact of tissue heterogeneities for these five high- to intermediate-energy sources in prostate and head & neck brachytherapy. METHODS AND MATERIALS: Treatment plans were generated for a cohort of prostate (n = 10) and oral tongue (n = 10) patients. Dose calculations were performed using RapidBrachyMCTPS, an in-house Geant4-based Monte Carlo treatment planning system. Treatment plans were simulated using 60Co, 192Ir, 75Se, 169Yb, and 153Gd as the active core of the microSelectron v2 source. Two dose calculation scenarios were presented: (1) dose to water in water (Dw,w), and (2) dose to medium in medium (Dm,m).
RESULTS: Dw,w overestimates planning target volume coverage compared with Dm,m, regardless of photon energy. The average planning target volume D90 reduction was ∼1% for high-energy sources, whereas larger differences were observed for intermediate-energy sources (1%-2% for prostate and 4%-7% for oral tongue). Dose differences were not clinically relevant (textless5%) for soft tissues in general. Going from Dw,w to Dm,m, bone doses were increased two- to three-fold for 169Yb and four- to five-fold for 153Gd, whereas the ratio was close to ∼1 for high-energy sources.
CONCLUSIONS: Dw,w underestimates the dose to bones and, to a lesser extent, overestimates the dose to soft tissues for radionuclides with average energies lower than 192Ir. Further studies regarding bone toxicities are needed before intermediate-energy sources can be adopted in cases where bones are in close vicinity to the tumor.
RESULTS: Dw,w overestimates planning target volume coverage compared with Dm,m, regardless of photon energy. The average planning target volume D90 reduction was ∼1% for high-energy sources, whereas larger differences were observed for intermediate-energy sources (1%-2% for prostate and 4%-7% for oral tongue). Dose differences were not clinically relevant (textless5%) for soft tissues in general. Going from Dw,w to Dm,m, bone doses were increased two- to three-fold for 169Yb and four- to five-fold for 153Gd, whereas the ratio was close to ∼1 for high-energy sources.
CONCLUSIONS: Dw,w underestimates the dose to bones and, to a lesser extent, overestimates the dose to soft tissues for radionuclides with average energies lower than 192Ir. Further studies regarding bone toxicities are needed before intermediate-energy sources can be adopted in cases where bones are in close vicinity to the tumor.
Kim, S. Peter; Cohalan, Claire; Juneau, Daniel; Enger, Shirin A.
Investigating the Self-calibration Factor for Yttrium-90 SPECT/CT Image-Based Dosimetry Radiation Presentation
Radiation Research Society, Winter Workshop in Big Sky, 04.03.2020.
BibTeX | Tags:
@misc{Kim2020,
title = {Investigating the Self-calibration Factor for Yttrium-90 SPECT/CT Image-Based Dosimetry Radiation},
author = {S. Peter Kim and Claire Cohalan and Daniel Juneau and Shirin A. Enger},
year = {2020},
date = {2020-03-04},
howpublished = {Radiation Research Society, Winter Workshop in Big Sky},
keywords = {},
pubstate = {published},
tppubtype = {presentation}
}
Famulari, Gabriel; Duclos, Marie; Enger, Shirin A.
A novel 169 Yb-based dynamic-shield intensity modulated brachytherapy delivery system for prostate cancer Journal Article
In: Medical Physics, vol. 47, no. 3, pp. 859–868, 2020, ISSN: 2473-4209.
Abstract | Links | BibTeX | Tags: Brachytherapy, Cohort Studies, Computer-Assisted, Humans, IMBT, Intensity-Modulated, Male, Monte Carlo, Monte Carlo Method, prostate cancer, Prostatic Neoplasms, Radioisotopes, Radiotherapy, Radiotherapy Planning, Uncertainty, Yb-169, Ytterbium
@article{famulari_novel_2020,
title = {A novel 169 Yb-based dynamic-shield intensity modulated brachytherapy delivery system for prostate cancer},
author = {Gabriel Famulari and Marie Duclos and Shirin A. Enger},
doi = {10.1002/mp.13959},
issn = {2473-4209},
year = {2020},
date = {2020-03-01},
journal = {Medical Physics},
volume = {47},
number = {3},
pages = {859--868},
abstract = {PURPOSE: Intensity modulated brachytherapy (IMBT) is a novel high dose rate brachytherapy (HDR BT) technique which incorporates static or dynamic shielding to increase tumor coverage and/or spare healthy tissues. The purpose of this study is to present a novel delivery system (AIM-Brachy) design that can enable dynamic-shield IMBT for prostate cancer.
METHODS: The AIM-Brachy system dynamically controls the rotation of platinum shields, placed within interstitial catheters, which partially collimate the radiation emitted from an 169 Yb source. Conventional HDR BT (10 Ci 192 Ir) and IMBT (18 Ci 169 Yb) plans were generated for 12 patients using an in-house column generation-based optimizer, coupled to a Geant4-based dose calculation engine, RapidBrachyMC. Treatment plans were normalized to match the same PTV D90 coverage as the clinical plan. Intershield attenuation effects were taken into account. A sensitivity analysis was performed to evaluate the dosimetric impact of systematic longitudinal source positioning errors ( ± 1 mm, ± 2 mm, and ± 3 mm) and rotational errors ( ± 5 ∘ , ± 10 ∘ , and ± 15 ∘ ) on clinically relevant parameters (PTV D90 and urethra D10 ).
RESULTS: The platinum shield reduced the dose rate on the shielded side at 1 cm to 18.1% of the dose rate on the unshielded side. For equal PTV D90 coverage, the urethral D10 was reduced by 13.3% ± 4.7%, without change to other plan quality indices (PTV V100 , V150, V200 , bladder V75 , rectum V75 , HI, COIN). Delivery times for HDR BT and IMBT were 9.2 ± 1.6 min and 18.6 ± 4.0 min, respectively. In general, the PTV D90 was more sensitive to source positioning errors than rotational errors, while the urethral D10 was more sensitive to rotational errors than source positioning errors. For a typical range of positioning errors ( ± 1 mm, ± 5 ∘ ), the overall tolerance was textless2%.
CONCLUSIONS: The AIM-Brachy system was proposed to deliver dynamic-shield IMBT for prostate cancer with the potential to create a low dose tunnel within the urethra. The urethra-sparing properties are desirable to minimize the occurrence and severity of urethral strictures or, alternatively, to provide a method for dose escalation.},
keywords = {Brachytherapy, Cohort Studies, Computer-Assisted, Humans, IMBT, Intensity-Modulated, Male, Monte Carlo, Monte Carlo Method, prostate cancer, Prostatic Neoplasms, Radioisotopes, Radiotherapy, Radiotherapy Planning, Uncertainty, Yb-169, Ytterbium},
pubstate = {published},
tppubtype = {article}
}
PURPOSE: Intensity modulated brachytherapy (IMBT) is a novel high dose rate brachytherapy (HDR BT) technique which incorporates static or dynamic shielding to increase tumor coverage and/or spare healthy tissues. The purpose of this study is to present a novel delivery system (AIM-Brachy) design that can enable dynamic-shield IMBT for prostate cancer.
METHODS: The AIM-Brachy system dynamically controls the rotation of platinum shields, placed within interstitial catheters, which partially collimate the radiation emitted from an 169 Yb source. Conventional HDR BT (10 Ci 192 Ir) and IMBT (18 Ci 169 Yb) plans were generated for 12 patients using an in-house column generation-based optimizer, coupled to a Geant4-based dose calculation engine, RapidBrachyMC. Treatment plans were normalized to match the same PTV D90 coverage as the clinical plan. Intershield attenuation effects were taken into account. A sensitivity analysis was performed to evaluate the dosimetric impact of systematic longitudinal source positioning errors ( ± 1 mm, ± 2 mm, and ± 3 mm) and rotational errors ( ± 5 ∘ , ± 10 ∘ , and ± 15 ∘ ) on clinically relevant parameters (PTV D90 and urethra D10 ).
RESULTS: The platinum shield reduced the dose rate on the shielded side at 1 cm to 18.1% of the dose rate on the unshielded side. For equal PTV D90 coverage, the urethral D10 was reduced by 13.3% ± 4.7%, without change to other plan quality indices (PTV V100 , V150, V200 , bladder V75 , rectum V75 , HI, COIN). Delivery times for HDR BT and IMBT were 9.2 ± 1.6 min and 18.6 ± 4.0 min, respectively. In general, the PTV D90 was more sensitive to source positioning errors than rotational errors, while the urethral D10 was more sensitive to rotational errors than source positioning errors. For a typical range of positioning errors ( ± 1 mm, ± 5 ∘ ), the overall tolerance was textless2%.
CONCLUSIONS: The AIM-Brachy system was proposed to deliver dynamic-shield IMBT for prostate cancer with the potential to create a low dose tunnel within the urethra. The urethra-sparing properties are desirable to minimize the occurrence and severity of urethral strictures or, alternatively, to provide a method for dose escalation.
METHODS: The AIM-Brachy system dynamically controls the rotation of platinum shields, placed within interstitial catheters, which partially collimate the radiation emitted from an 169 Yb source. Conventional HDR BT (10 Ci 192 Ir) and IMBT (18 Ci 169 Yb) plans were generated for 12 patients using an in-house column generation-based optimizer, coupled to a Geant4-based dose calculation engine, RapidBrachyMC. Treatment plans were normalized to match the same PTV D90 coverage as the clinical plan. Intershield attenuation effects were taken into account. A sensitivity analysis was performed to evaluate the dosimetric impact of systematic longitudinal source positioning errors ( ± 1 mm, ± 2 mm, and ± 3 mm) and rotational errors ( ± 5 ∘ , ± 10 ∘ , and ± 15 ∘ ) on clinically relevant parameters (PTV D90 and urethra D10 ).
RESULTS: The platinum shield reduced the dose rate on the shielded side at 1 cm to 18.1% of the dose rate on the unshielded side. For equal PTV D90 coverage, the urethral D10 was reduced by 13.3% ± 4.7%, without change to other plan quality indices (PTV V100 , V150, V200 , bladder V75 , rectum V75 , HI, COIN). Delivery times for HDR BT and IMBT were 9.2 ± 1.6 min and 18.6 ± 4.0 min, respectively. In general, the PTV D90 was more sensitive to source positioning errors than rotational errors, while the urethral D10 was more sensitive to rotational errors than source positioning errors. For a typical range of positioning errors ( ± 1 mm, ± 5 ∘ ), the overall tolerance was textless2%.
CONCLUSIONS: The AIM-Brachy system was proposed to deliver dynamic-shield IMBT for prostate cancer with the potential to create a low dose tunnel within the urethra. The urethra-sparing properties are desirable to minimize the occurrence and severity of urethral strictures or, alternatively, to provide a method for dose escalation.
Morcos, Marc; Enger, Shirin A.
Monte Carlo dosimetry study of novel rotating MRI-compatible shielded tandems for intensity modulated cervix brachytherapy 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. 71, pp. 178–184, 2020, ISSN: 1724-191X.
Abstract | Links | BibTeX | Tags: Anisotropy, Brachytherapy, Female, Humans, Image-guided cervix brachytherapy, Intensity modulated brachytherapy, Intensity-Modulated, Iridium Radioisotopes, Magnetic Resonance Imaging, Monte Carlo based dosimetry, Monte Carlo Method, MRI-guided GYN brachytherapy, Radiometry, Radiotherapy, Selenium Radioisotopes, Uterine Cervical Neoplasms, Ytterbium
@article{morcos_monte_2020,
title = {Monte Carlo dosimetry study of novel rotating MRI-compatible shielded tandems for intensity modulated cervix brachytherapy},
author = {Marc Morcos and Shirin A. Enger},
doi = {10.1016/j.ejmp.2020.02.014},
issn = {1724-191X},
year = {2020},
date = {2020-03-01},
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 = {71},
pages = {178--184},
abstract = {PURPOSE: Intensity modulated brachytherapy (IMBT) with rotating metal shields enables dose modulation that can better conform to the tumor while reducing OAR doses. In this work, we investigate novel rotating shields, compatible with MRI-compatible tandems used for cervix brachytherapy. Three unique shields were evaluated using the traditional 192Ir source. Additionally, 75Se and 169Yb isotopes were investigated as alternative sources.
METHODS: Three different IMBT shields were modeled and simulated in RapidBrachyMCTPS. Each tungsten shield was designed to fit inside a 6 mm-wide MRI-compatible tandem. The active core of the source was replaced with 192Ir, 75Se and 169Yb. Transmission factors (TFs) were calculated and defined as the dose ratio at 1 cm on opposite sides of the shielded tandem on the transverse plane. Polar and azimuthal anisotropy plots were extracted from simulations. Dose homogeneities V200%V100% were calculated for all radionuclide-shield combinations.
RESULTS: TFs are favorable for IMBT and ranged between 12.9% and 32.2% for 192Ir, 4.0%-16.1% for 75Se and 1.2-6.4% for 169Yb for all shield designs. Average beam-widths in the polar and azimuthal directions were reduced to the range of 42°-112° and 27°-107°, respectively, for all shield-radionuclide combinations. Dose homogeneities for all the radionuclide-shield combinations were within 12% of the non-IMBT tandem.
CONCLUSIONS: This study has quantitatively assessed the influence of various rotating cervical cancer-specific IMBT tandem shields on dosimetry. The dynamic single-channel shields and narrow beam-widths in the polar and azimuthal direction give rise to highly anisotropic distributions. Intermediate-to-high energy radionuclides, 75Se and 169Yb substantially improve the modulation capacity of IMBT and pave the way for treating large and complex cervical cancer without interstitial needle implantation.},
keywords = {Anisotropy, Brachytherapy, Female, Humans, Image-guided cervix brachytherapy, Intensity modulated brachytherapy, Intensity-Modulated, Iridium Radioisotopes, Magnetic Resonance Imaging, Monte Carlo based dosimetry, Monte Carlo Method, MRI-guided GYN brachytherapy, Radiometry, Radiotherapy, Selenium Radioisotopes, Uterine Cervical Neoplasms, Ytterbium},
pubstate = {published},
tppubtype = {article}
}
PURPOSE: Intensity modulated brachytherapy (IMBT) with rotating metal shields enables dose modulation that can better conform to the tumor while reducing OAR doses. In this work, we investigate novel rotating shields, compatible with MRI-compatible tandems used for cervix brachytherapy. Three unique shields were evaluated using the traditional 192Ir source. Additionally, 75Se and 169Yb isotopes were investigated as alternative sources.
METHODS: Three different IMBT shields were modeled and simulated in RapidBrachyMCTPS. Each tungsten shield was designed to fit inside a 6 mm-wide MRI-compatible tandem. The active core of the source was replaced with 192Ir, 75Se and 169Yb. Transmission factors (TFs) were calculated and defined as the dose ratio at 1 cm on opposite sides of the shielded tandem on the transverse plane. Polar and azimuthal anisotropy plots were extracted from simulations. Dose homogeneities V200%V100% were calculated for all radionuclide-shield combinations.
RESULTS: TFs are favorable for IMBT and ranged between 12.9% and 32.2% for 192Ir, 4.0%-16.1% for 75Se and 1.2-6.4% for 169Yb for all shield designs. Average beam-widths in the polar and azimuthal directions were reduced to the range of 42°-112° and 27°-107°, respectively, for all shield-radionuclide combinations. Dose homogeneities for all the radionuclide-shield combinations were within 12% of the non-IMBT tandem.
CONCLUSIONS: This study has quantitatively assessed the influence of various rotating cervical cancer-specific IMBT tandem shields on dosimetry. The dynamic single-channel shields and narrow beam-widths in the polar and azimuthal direction give rise to highly anisotropic distributions. Intermediate-to-high energy radionuclides, 75Se and 169Yb substantially improve the modulation capacity of IMBT and pave the way for treating large and complex cervical cancer without interstitial needle implantation.
METHODS: Three different IMBT shields were modeled and simulated in RapidBrachyMCTPS. Each tungsten shield was designed to fit inside a 6 mm-wide MRI-compatible tandem. The active core of the source was replaced with 192Ir, 75Se and 169Yb. Transmission factors (TFs) were calculated and defined as the dose ratio at 1 cm on opposite sides of the shielded tandem on the transverse plane. Polar and azimuthal anisotropy plots were extracted from simulations. Dose homogeneities V200%V100% were calculated for all radionuclide-shield combinations.
RESULTS: TFs are favorable for IMBT and ranged between 12.9% and 32.2% for 192Ir, 4.0%-16.1% for 75Se and 1.2-6.4% for 169Yb for all shield designs. Average beam-widths in the polar and azimuthal directions were reduced to the range of 42°-112° and 27°-107°, respectively, for all shield-radionuclide combinations. Dose homogeneities for all the radionuclide-shield combinations were within 12% of the non-IMBT tandem.
CONCLUSIONS: This study has quantitatively assessed the influence of various rotating cervical cancer-specific IMBT tandem shields on dosimetry. The dynamic single-channel shields and narrow beam-widths in the polar and azimuthal direction give rise to highly anisotropic distributions. Intermediate-to-high energy radionuclides, 75Se and 169Yb substantially improve the modulation capacity of IMBT and pave the way for treating large and complex cervical cancer without interstitial needle implantation.