award
2022
McGill Faculty of Medicine and Health Sciences Internal Studentship award
2022.
@award{nokey,
title = {McGill Faculty of Medicine and Health Sciences Internal Studentship},
author = {Jonathan Kalinowski},
url = {https://www.mcgill.ca/medhealthsci-gradstudies/funding-opportunities/graduate-students/internal-studentships},
year = {2022},
date = {2022-08-15},
urldate = {2022-08-15},
organization = {McGill University Faculty of Medicine and Health Sciences},
abstract = {Internal Studentships are open to highly qualified Faculty of Medicine graduate students who are registered full-time in a research training program (Thesis) leading to an M.Sc or PhD degree.
},
keywords = {},
pubstate = {published},
tppubtype = {award}
}
Internal Studentships are open to highly qualified Faculty of Medicine graduate students who are registered full-time in a research training program (Thesis) leading to an M.Sc or PhD degree.
Graduate Excellence Award award
2022.
@award{nokey,
title = {Graduate Excellence Award },
author = {Maryam Rahbaran},
year = {2022},
date = {2022-08-08},
abstract = {Merit-based recruitment award for first year MSc students. },
keywords = {},
pubstate = {published},
tppubtype = {award}
}
Merit-based recruitment award for first year MSc students. Fonds de recherche du Québec – Santé (FRQS) PhD doctoral training scholarship award
2022, ($84,000 for 2022 – 2026).
@award{nokey,
title = {Fonds de recherche du Québec - Santé (FRQS) PhD doctoral training scholarship},
author = {Yujing Zou},
url = {https://repertoire.frq.gouv.qc.ca/offres/rechercheOffres.do?methode=afficher},
year = {2022},
date = {2022-06-02},
urldate = {2022-06-02},
organization = {Fonds de recherche du Québec},
note = {$84,000 for 2022 - 2026},
keywords = {},
pubstate = {published},
tppubtype = {award}
}
Fonds de recherche du Québec – Nature et technologies (FRQNT) PhD doctoral training scholarship award
2022, ($84,000 for 2022 – 2026; Declined due to acceptance of FRQS).
@award{nokey,
title = {Fonds de recherche du Québec - Nature et technologies (FRQNT) PhD doctoral training scholarship},
author = {Yujing Zou},
url = {https://repertoire.frq.gouv.qc.ca/offres/rechercheOffres.do?methode=afficher},
year = {2022},
date = {2022-06-02},
urldate = {2022-06-02},
organization = {Fonds de recherche du Québec},
note = {$84,000 for 2022 - 2026; Declined due to acceptance of FRQS},
keywords = {},
pubstate = {published},
tppubtype = {award}
}
Young Investigator Competition Winner at the Curietherapies Conference award
2022.
@award{nokey,
title = {Young Investigator Competition Winner at the Curietherapies Conference },
author = {Yujing Zou and Magali Lecavalier-Barsoum and Manuela Pelmus and Farhad Maleki and Shirin A. Enger },
url = {https://www.researchgate.net/publication/360979157_SP-0014_McMedHacks_Deep_learning_for_medical_image_analysis_workshops_and_Hackathon_in_radiation_oncology},
year = {2022},
date = {2022-05-23},
urldate = {2022-05-23},
organization = {Curietherapies},
abstract = {Purpose/Objective: The McMedHacks workshop and presentation series was created to teach individuals from various backgrounds about deep learning (DL) for medical image analysis in May, 2021. Material/Methods: McMedHacks is a free and student-led 8-week summer program. Registration for the event was open to everyone, including a form to survey participants’ area of expertise, country of origin, level of study, and level of programming skills. The weekly workshops were instructed by 8 students and experts assisted by 20 mentors who provided weekly tutorials. Recent developments in DL and medical physics were highlighted by 21 leaders from industry and academia. A virtual grand challenge Hackathon took place at the end of the workshop series. All events were held virtually and recorded on Zoom to accommodate all time zones and locations. The workshops were designed as interactive coding demos and shared through Google Colab notebooks. Results: McMedHacks gained 356 registrations from participants of 38 different countries (Fig. 1) from undergraduates, to PhDs and MDs. A vast number of disciplines and professions were represented, dominated by medical physics students, academic, and clinical medical physicists (Fig. 2). Sixty-nine participants earned a certificate of completion by having engaged with at least 12 of all 14 events. The program received participant feedback average scores of 4.768, 4.478, 4.579, 4.292, 4.84 out of five for the qualities of presentation, workshop session, tutorial and mentor, assignments, and course delivery, respectively. The eight-week long workshop’s duration allowed participants to digest the taught materials in a continuous manner as opposed to bootcamp-style conference workshops. Conclusion: The overwhelming interest and engagement for the McMedHacks workshop series from the Radiation Oncology (RadOnc) community illustrates a demand for Artificial Intelligence (AI) education in RadOnc. The future of RadOnc clinics will inevitably integrate AI. Therefore, current RadOnc professionals, and student and resident trainees should be prepared to understand basic AI principles and its applications to troubleshoot, innovate, and collaborate. McMedHacks set an excellent example of promoting open and multidisciplinary education, scientific communication, and leadership for integrating AI education into the RadOnc community on an international level. Therefore, we advocate for implementation of AI curriculums in professional education programs such as Commission on Accreditation of Medical Physics Education Programs (CAMPEP). Furthermore, we encourage experts from around the world in the field of AI, or RadOnc, or both, to take initiatives like McMedHacks to collaborate and push forward AI education in their departments and lead practical workshops, regardless of their levels of education.},
keywords = {},
pubstate = {published},
tppubtype = {award}
}
Purpose/Objective: The McMedHacks workshop and presentation series was created to teach individuals from various backgrounds about deep learning (DL) for medical image analysis in May, 2021. Material/Methods: McMedHacks is a free and student-led 8-week summer program. Registration for the event was open to everyone, including a form to survey participants’ area of expertise, country of origin, level of study, and level of programming skills. The weekly workshops were instructed by 8 students and experts assisted by 20 mentors who provided weekly tutorials. Recent developments in DL and medical physics were highlighted by 21 leaders from industry and academia. A virtual grand challenge Hackathon took place at the end of the workshop series. All events were held virtually and recorded on Zoom to accommodate all time zones and locations. The workshops were designed as interactive coding demos and shared through Google Colab notebooks. Results: McMedHacks gained 356 registrations from participants of 38 different countries (Fig. 1) from undergraduates, to PhDs and MDs. A vast number of disciplines and professions were represented, dominated by medical physics students, academic, and clinical medical physicists (Fig. 2). Sixty-nine participants earned a certificate of completion by having engaged with at least 12 of all 14 events. The program received participant feedback average scores of 4.768, 4.478, 4.579, 4.292, 4.84 out of five for the qualities of presentation, workshop session, tutorial and mentor, assignments, and course delivery, respectively. The eight-week long workshop’s duration allowed participants to digest the taught materials in a continuous manner as opposed to bootcamp-style conference workshops. Conclusion: The overwhelming interest and engagement for the McMedHacks workshop series from the Radiation Oncology (RadOnc) community illustrates a demand for Artificial Intelligence (AI) education in RadOnc. The future of RadOnc clinics will inevitably integrate AI. Therefore, current RadOnc professionals, and student and resident trainees should be prepared to understand basic AI principles and its applications to troubleshoot, innovate, and collaborate. McMedHacks set an excellent example of promoting open and multidisciplinary education, scientific communication, and leadership for integrating AI education into the RadOnc community on an international level. Therefore, we advocate for implementation of AI curriculums in professional education programs such as Commission on Accreditation of Medical Physics Education Programs (CAMPEP). Furthermore, we encourage experts from around the world in the field of AI, or RadOnc, or both, to take initiatives like McMedHacks to collaborate and push forward AI education in their departments and lead practical workshops, regardless of their levels of education.Biological & Biomedical Engineering PhD Recruitment Award award
2022, (These awards are designed to help recruit top students to our program and are offered to applicants wishing to start in Fall or Winter. The standard recruitment awards are $10,000/year for three years for Doctoral students.).
@award{nokey,
title = {Biological & Biomedical Engineering PhD Recruitment Award },
author = {Yujing Zou},
url = {https://www.mcgill.ca/bbme/programs/funding#BME-Recruitment-Award},
year = {2022},
date = {2022-05-10},
urldate = {2022-05-10},
organization = {McGill Biological & Biomedical Engineering department },
note = {These awards are designed to help recruit top students to our program and are offered to applicants wishing to start in Fall or Winter. The standard recruitment awards are $10,000/year for three years for Doctoral students.},
keywords = {},
pubstate = {published},
tppubtype = {award}
}
Biological & Biomedical Engineering PhD Recruitment Award award
2022.
@award{nokey,
title = {Biological & Biomedical Engineering PhD Recruitment Award },
author = {Hossein Jafarzadeh },
url = {https://www.mcgill.ca/bbme/programs/funding#BME-Recruitment-Award},
year = {2022},
date = {2022-05-10},
keywords = {},
pubstate = {published},
tppubtype = {award}
}
Graduate Research Enhancement and Travel Awards (GREAT Awards) award
2022, (In 2009, Graduate and Postdoctoral Studies introduced the Graduate Research Enhancement and Travel awards (GREAT awards) program in consultation with the Faculty Deans and Associate Deans. These awards cover dissemination of research through graduate student presentations at conferences, and other graduate student research-enhancement activities, such as travel for fieldwork, archival inquiry and extra-mural collaborative research. GREAT budgets are allocated to Faculties each year, and as such, are managed directly by the Associate Dean’s office.).
@award{nokey,
title = {Graduate Research Enhancement and Travel Awards (GREAT Awards)},
author = {Yujing Zou},
url = {https://www.mcgill.ca/gps/funding/fac-staff/awards/great},
year = {2022},
date = {2022-04-14},
note = {In 2009, Graduate and Postdoctoral Studies introduced the Graduate Research Enhancement and Travel awards (GREAT awards) program in consultation with the Faculty Deans and Associate Deans. These awards cover dissemination of research through graduate student presentations at conferences, and other graduate student research-enhancement activities, such as travel for fieldwork, archival inquiry and extra-mural collaborative research. GREAT budgets are allocated to Faculties each year, and as such, are managed directly by the Associate Dean's office.},
keywords = {},
pubstate = {published},
tppubtype = {award}
}
Second prize at the International Conference on Monte Carlo Techniques for Medical Applications award
2022.
@award{nokey,
title = {Second prize at the International Conference on Monte Carlo Techniques for Medical Applications },
author = {Liam Carroll and Shirin A. Enger},
year = {2022},
date = {2022-04-13},
urldate = {2022-04-13},
journal = {International Conference on Monte Carlo Techniques for Medical Applications },
abstract = {Introduction
Geant4[1] is a Monte Carlo toolkit that provides a flexible platform to design radiation transport simulations. This flexibility requires a high level of complexity when writing new user-codes. New users must undergo extensive training to begin writing useful simulations. The aim of this study was to develop a modular radiation simulation software package called MaRSS based on Geant4 user-code to serve as both an educational tool and as a simulation tool for medical radiation detector simulations.
Materials & Methods
MaRSS builds on Geant4 using Penelope electromagnetic physics models and cross-sections[2]. To give the users possibility to change simulation parameters without changing the source code, MaRSS is equipped with a set of messenger classes which are intercom modules provided by Geant4 to configure applications and provide user interactivity with the code. These messenger classes add additional user commands that can be used to add or remove volumes from the simulation geometry and associated sensitive detectors. The sensitive detectors are objects that Geant4 uses to save simulation results. A number of default volumes and detectors are included in MaRSS that can be used for the design of scintillating fiber-based radiation detectors. MaRSS adds to the existing Geant4 sensitive detector code by creating a new base class called RunSD that is inherited by all sensitive detector objects. RunSD is implemented such that the code needed to initialize a sensitive detector is included in two classes, normally, this code is spread out in several classes. A similar approach is taken with geometrical volumes. To validate MaRSS, range in water of positrons emitted from four radioisotopes commonly used for positron emission tomography was calculated and compared with published work: Fluorine-18 (18F), Carbon-11 (11C), Oxygen-15 (15O) and Gallium-68 (68Ga). A sphere with a radius of 1 m was filed with water. For each radioisotope, 100 million decay events were simulated originating at the center of the simulated water sphere. The resulting positrons were allowed to annihilate. Two energy cuts were simulated, 1 keV and 0.1 keV. Two histograms were created, one using the annihilation locations and another with the energy of the emitted positrons. Results were compared with published positron range values calculated with a PENELOPE[2]-based Monte Carlo software called PeneloPET [3], an analytical expression to estimate the range of positrons described by Cal-Gonzales et.al.[3], a simulation by Lehnert et. al. [4] written using GATE[5] and a separate Monte Carlo software written by Champion and Le Loirec[6] that directly simulates the formation of positronium in water to calculate positron range.
Results
Figure 1 shows the mean calculated positron ranges and calculated positron emission energies compared to literature values. Simulated positron energy means were within 1.8% of literature values. Simulated ranges were within 2% of GATE simulation[4].
References
[1] S. Agostinelli et al., “Geant4—a simulation toolkit,” Nucl. Instruments Methods Phys. Res. Sect. A Accel. Spectrometers, Detect. Assoc. Equip., vol. 506, no. 3, pp. 250–303, Jul. 2003.
[2] J. Baró, J. Sempau, J. M. Fernández-Varea, and F. Salvat, “PENELOPE: An algorithm for Monte Carlo simulation of the penetration and energy loss of electrons and positrons in matter,” Nucl. Inst. Methods Phys. Res. B, vol. 100, no. 1, pp. 31–46, May 1995.
[3] J. Cal-González et al., “Positron range estimations with PeneloPET,” Phys. Med. Biol., vol. 58, no. 15, pp. 5127–5152, 2013.
[4] W. Lehnert, M.-C. Gregoire, A. Reilhac, and S. R. Meikle, “Analytical positron range modelling in heterogeneous media for PET Monte Carlo simulation,” Phys. Med. Biol., vol. 56, no. 11, p. 3313, May 2011.
[5] D. Strul, G. Santin, D. Lazaro, V. Breton, and C. Morel, “GATE (geant4 application for tomographic emission): a PET/SPECT general-purpose simulation platform,” Nucl. Phys. B - Proc. Suppl., vol. 125, pp. 75–79, Sep. 2003.
[6] C. Champion and C. Le Loirec, “Positron follow-up in liquid water: II. Spatial and energetic study for the most important radioisotopes used in PET,” Phys. Med. Biol., vol. 52, no. 22, pp. 6605–6625, Nov. 2007.
},
keywords = {},
pubstate = {published},
tppubtype = {award}
}
Introduction
Geant4[1] is a Monte Carlo toolkit that provides a flexible platform to design radiation transport simulations. This flexibility requires a high level of complexity when writing new user-codes. New users must undergo extensive training to begin writing useful simulations. The aim of this study was to develop a modular radiation simulation software package called MaRSS based on Geant4 user-code to serve as both an educational tool and as a simulation tool for medical radiation detector simulations.
Materials & Methods
MaRSS builds on Geant4 using Penelope electromagnetic physics models and cross-sections[2]. To give the users possibility to change simulation parameters without changing the source code, MaRSS is equipped with a set of messenger classes which are intercom modules provided by Geant4 to configure applications and provide user interactivity with the code. These messenger classes add additional user commands that can be used to add or remove volumes from the simulation geometry and associated sensitive detectors. The sensitive detectors are objects that Geant4 uses to save simulation results. A number of default volumes and detectors are included in MaRSS that can be used for the design of scintillating fiber-based radiation detectors. MaRSS adds to the existing Geant4 sensitive detector code by creating a new base class called RunSD that is inherited by all sensitive detector objects. RunSD is implemented such that the code needed to initialize a sensitive detector is included in two classes, normally, this code is spread out in several classes. A similar approach is taken with geometrical volumes. To validate MaRSS, range in water of positrons emitted from four radioisotopes commonly used for positron emission tomography was calculated and compared with published work: Fluorine-18 (18F), Carbon-11 (11C), Oxygen-15 (15O) and Gallium-68 (68Ga). A sphere with a radius of 1 m was filed with water. For each radioisotope, 100 million decay events were simulated originating at the center of the simulated water sphere. The resulting positrons were allowed to annihilate. Two energy cuts were simulated, 1 keV and 0.1 keV. Two histograms were created, one using the annihilation locations and another with the energy of the emitted positrons. Results were compared with published positron range values calculated with a PENELOPE[2]-based Monte Carlo software called PeneloPET [3], an analytical expression to estimate the range of positrons described by Cal-Gonzales et.al.[3], a simulation by Lehnert et. al. [4] written using GATE[5] and a separate Monte Carlo software written by Champion and Le Loirec[6] that directly simulates the formation of positronium in water to calculate positron range.
Results
Figure 1 shows the mean calculated positron ranges and calculated positron emission energies compared to literature values. Simulated positron energy means were within 1.8% of literature values. Simulated ranges were within 2% of GATE simulation[4].
References
[1] S. Agostinelli et al., “Geant4—a simulation toolkit,” Nucl. Instruments Methods Phys. Res. Sect. A Accel. Spectrometers, Detect. Assoc. Equip., vol. 506, no. 3, pp. 250–303, Jul. 2003.
[2] J. Baró, J. Sempau, J. M. Fernández-Varea, and F. Salvat, “PENELOPE: An algorithm for Monte Carlo simulation of the penetration and energy loss of electrons and positrons in matter,” Nucl. Inst. Methods Phys. Res. B, vol. 100, no. 1, pp. 31–46, May 1995.
[3] J. Cal-González et al., “Positron range estimations with PeneloPET,” Phys. Med. Biol., vol. 58, no. 15, pp. 5127–5152, 2013.
[4] W. Lehnert, M.-C. Gregoire, A. Reilhac, and S. R. Meikle, “Analytical positron range modelling in heterogeneous media for PET Monte Carlo simulation,” Phys. Med. Biol., vol. 56, no. 11, p. 3313, May 2011.
[5] D. Strul, G. Santin, D. Lazaro, V. Breton, and C. Morel, “GATE (geant4 application for tomographic emission): a PET/SPECT general-purpose simulation platform,” Nucl. Phys. B – Proc. Suppl., vol. 125, pp. 75–79, Sep. 2003.
[6] C. Champion and C. Le Loirec, “Positron follow-up in liquid water: II. Spatial and energetic study for the most important radioisotopes used in PET,” Phys. Med. Biol., vol. 52, no. 22, pp. 6605–6625, Nov. 2007.
2021
T I Gurman Prize in Physics award
2021.
@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.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}
}
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}
}
Merit-based recruitment award for first year MSc students. award
2021.
@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}
}
Mitacs Globalink Research Award award
2021.
@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. 2021.
@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/2020
Graduate Excellence Fellowship award
2020.
@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}
}
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}
}
First prize for best presentation at the congrès annuel de l’AQPMC award
2020.
@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.Math And Physics Class Of 1965 Prize award
2020.
@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. Excellence Award from Department of Biological and Biomedical Engineering award
2020.
@award{Carroll2020,
title = {Excellence Award from Department of Biological and Biomedical Engineering},
author = {Liam Carroll},
year = {2020},
date = {2020-01-01},
urldate = {2020-01-01},
organization = {McGill University},
school = {Bioengineering and Biomedical Engineering Program},
abstract = {The award recognizes excellent performance in the PhD Program of the BBME/BME graduate program. The selection is based on a combination of overall excellence, performance in the program, grades, progress in project and publications. },
howpublished = {Department of Biological and Biomedical Engineering},
keywords = {award},
pubstate = {published},
tppubtype = {award}
}
The award recognizes excellent performance in the PhD Program of the BBME/BME graduate program. The selection is based on a combination of overall excellence, performance in the program, grades, progress in project and publications. 2019
Canada Research Chair Tier II in Medical Physics award
2019.
@award{Enger2019,
title = {Canada Research Chair Tier II in Medical Physics},
author = {Shirin A. Enger },
year = {2019},
date = {2019-10-01},
urldate = {2019-10-01},
organization = {Government of Canada},
keywords = {},
pubstate = {published},
tppubtype = {award}
}
Development of an in-vivo radiation dosimeter for radiotherapy. Winner of the best in Physics Award. award
2019.
@award{Mégrourèche2019,
title = {Development of an in-vivo radiation dosimeter for radiotherapy. Winner of the best in Physics Award.},
author = {Julien Mégrourèche and Lilian Childress and Jack Sankey and Alaina Bui and Shirin A. Enger},
year = {2019},
date = {2019-10-01},
urldate = {2019-10-01},
howpublished = {Radiation Association of Radiation Oncology (CARO)},
keywords = {award},
pubstate = {published},
tppubtype = {award}
}
Development of a hydrated electron dosimeter for in vivo applications in radiotherapy: A proof of concept. Winner of the J.R. Cunningham Young Investigators Award award
2019.
@award{Mégrourèche2019b,
title = {Development of a hydrated electron dosimeter for in vivo applications in radiotherapy: A proof of concept. Winner of the J.R. Cunningham Young Investigators Award},
author = {Julien Mégrourèche and Lilian Childress and Jack Sankey and Alaina Bui and Shirin A. Enger },
year = {2019},
date = {2019-09-01},
urldate = {2019-09-01},
howpublished = {Canadian Organization of Medical Physicists (COMP)},
keywords = {award},
pubstate = {published},
tppubtype = {award}
}
Winners of the Centech propulsion program award
2019.
@award{Carroll2019,
title = {Winners of the Centech propulsion program},
author = {Liam Carroll and Gustavo Kertzscher and Shirin A. Enger},
year = {2019},
date = {2019-01-01},
urldate = {2019-01-01},
organization = {Centech},
abstract = {Two years’ business incubator, (50 k CAD) + access to consulting firms to build a commercial version of BetaSense that can be used in a clinical environment for patient measurements. },
keywords = {award},
pubstate = {published},
tppubtype = {award}
}
Two years’ business incubator, (50 k CAD) + access to consulting firms to build a commercial version of BetaSense that can be used in a clinical environment for patient measurements. Winners of the Marika Zelenka Roy Innovation Prize award
2019.
@award{Carroll2019b,
title = {Winners of the Marika Zelenka Roy Innovation Prize},
author = {Liam Carroll and Gustavo Kertzscher and Shirin A. Enger},
year = {2019},
date = {2019-01-01},
urldate = {2019-01-01},
organization = {McGill University},
abstract = {(50 k CAD) at McGill University Clinical Innovation Competition for the detector BetaSense (A non-invasive positron detector to measure the arterial input function for pharmacokinetic modelling in dynamic positron emission tomography imaging). },
howpublished = {McGill University Clinical Innovation Competition},
keywords = {award},
pubstate = {published},
tppubtype = {award}
}
(50 k CAD) at McGill University Clinical Innovation Competition for the detector BetaSense (A non-invasive positron detector to measure the arterial input function for pharmacokinetic modelling in dynamic positron emission tomography imaging). Young Investigator Competition Award – Urethra-Sparing with Intensity Modulated Brachytherapy for Prostate Cancer award
2019.
@award{Famulari2019,
title = {Young Investigator Competition Award - Urethra-Sparing with Intensity Modulated Brachytherapy for Prostate Cancer},
author = {Gabriel Famulari and Shirin A. Enger},
year = {2019},
date = {2019-01-01},
urldate = {2019-01-01},
howpublished = {Curietherapies 2019},
keywords = {award},
pubstate = {published},
tppubtype = {award}
}
2nd prize in the Young Investigator Competition award
2019.
@award{Mégrourèche2019c,
title = {2nd prize in the Young Investigator Competition},
author = {Julien Mégrourèche and Alaina Bui and Jack Sankey and Lilian Childress and Shirin A. Enger},
year = {2019},
date = {2019-01-01},
urldate = {2019-01-01},
organization = {McGill University Health Center},
abstract = {Development of a Hydrated Electron Dosimeter for Radiotherapy
Applications: A Proof of Concept. 2nd prize in the Young Investigator Competition award at the Research Institute of McGill University Health Center, Cancer Research program.},
howpublished = {Research Institute of McGill University Health Center},
keywords = {award},
pubstate = {published},
tppubtype = {award}
}
Development of a Hydrated Electron Dosimeter for Radiotherapy
Applications: A Proof of Concept. 2nd prize in the Young Investigator Competition award at the Research Institute of McGill University Health Center, Cancer Research program.0000
[No title] award
0000.
@award{nokey,
title = {[No title]},
keywords = {},
pubstate = {published},
tppubtype = {award}
}
award
2022
McGill Faculty of Medicine and Health Sciences Internal Studentship award
2022.
@award{nokey,
title = {McGill Faculty of Medicine and Health Sciences Internal Studentship},
author = {Jonathan Kalinowski},
url = {https://www.mcgill.ca/medhealthsci-gradstudies/funding-opportunities/graduate-students/internal-studentships},
year = {2022},
date = {2022-08-15},
urldate = {2022-08-15},
organization = {McGill University Faculty of Medicine and Health Sciences},
abstract = {Internal Studentships are open to highly qualified Faculty of Medicine graduate students who are registered full-time in a research training program (Thesis) leading to an M.Sc or PhD degree.
},
keywords = {},
pubstate = {published},
tppubtype = {award}
}
Internal Studentships are open to highly qualified Faculty of Medicine graduate students who are registered full-time in a research training program (Thesis) leading to an M.Sc or PhD degree.
Graduate Excellence Award award
2022.
@award{nokey,
title = {Graduate Excellence Award },
author = {Maryam Rahbaran},
year = {2022},
date = {2022-08-08},
abstract = {Merit-based recruitment award for first year MSc students. },
keywords = {},
pubstate = {published},
tppubtype = {award}
}
Merit-based recruitment award for first year MSc students.
Fonds de recherche du Québec – Santé (FRQS) PhD doctoral training scholarship award
2022, ($84,000 for 2022 – 2026).
@award{nokey,
title = {Fonds de recherche du Québec - Santé (FRQS) PhD doctoral training scholarship},
author = {Yujing Zou},
url = {https://repertoire.frq.gouv.qc.ca/offres/rechercheOffres.do?methode=afficher},
year = {2022},
date = {2022-06-02},
urldate = {2022-06-02},
organization = {Fonds de recherche du Québec},
note = {$84,000 for 2022 - 2026},
keywords = {},
pubstate = {published},
tppubtype = {award}
}
Fonds de recherche du Québec – Nature et technologies (FRQNT) PhD doctoral training scholarship award
2022, ($84,000 for 2022 – 2026; Declined due to acceptance of FRQS).
@award{nokey,
title = {Fonds de recherche du Québec - Nature et technologies (FRQNT) PhD doctoral training scholarship},
author = {Yujing Zou},
url = {https://repertoire.frq.gouv.qc.ca/offres/rechercheOffres.do?methode=afficher},
year = {2022},
date = {2022-06-02},
urldate = {2022-06-02},
organization = {Fonds de recherche du Québec},
note = {$84,000 for 2022 - 2026; Declined due to acceptance of FRQS},
keywords = {},
pubstate = {published},
tppubtype = {award}
}
Young Investigator Competition Winner at the Curietherapies Conference award
2022.
@award{nokey,
title = {Young Investigator Competition Winner at the Curietherapies Conference },
author = {Yujing Zou and Magali Lecavalier-Barsoum and Manuela Pelmus and Farhad Maleki and Shirin A. Enger },
url = {https://www.researchgate.net/publication/360979157_SP-0014_McMedHacks_Deep_learning_for_medical_image_analysis_workshops_and_Hackathon_in_radiation_oncology},
year = {2022},
date = {2022-05-23},
urldate = {2022-05-23},
organization = {Curietherapies},
abstract = {Purpose/Objective: The McMedHacks workshop and presentation series was created to teach individuals from various backgrounds about deep learning (DL) for medical image analysis in May, 2021. Material/Methods: McMedHacks is a free and student-led 8-week summer program. Registration for the event was open to everyone, including a form to survey participants’ area of expertise, country of origin, level of study, and level of programming skills. The weekly workshops were instructed by 8 students and experts assisted by 20 mentors who provided weekly tutorials. Recent developments in DL and medical physics were highlighted by 21 leaders from industry and academia. A virtual grand challenge Hackathon took place at the end of the workshop series. All events were held virtually and recorded on Zoom to accommodate all time zones and locations. The workshops were designed as interactive coding demos and shared through Google Colab notebooks. Results: McMedHacks gained 356 registrations from participants of 38 different countries (Fig. 1) from undergraduates, to PhDs and MDs. A vast number of disciplines and professions were represented, dominated by medical physics students, academic, and clinical medical physicists (Fig. 2). Sixty-nine participants earned a certificate of completion by having engaged with at least 12 of all 14 events. The program received participant feedback average scores of 4.768, 4.478, 4.579, 4.292, 4.84 out of five for the qualities of presentation, workshop session, tutorial and mentor, assignments, and course delivery, respectively. The eight-week long workshop’s duration allowed participants to digest the taught materials in a continuous manner as opposed to bootcamp-style conference workshops. Conclusion: The overwhelming interest and engagement for the McMedHacks workshop series from the Radiation Oncology (RadOnc) community illustrates a demand for Artificial Intelligence (AI) education in RadOnc. The future of RadOnc clinics will inevitably integrate AI. Therefore, current RadOnc professionals, and student and resident trainees should be prepared to understand basic AI principles and its applications to troubleshoot, innovate, and collaborate. McMedHacks set an excellent example of promoting open and multidisciplinary education, scientific communication, and leadership for integrating AI education into the RadOnc community on an international level. Therefore, we advocate for implementation of AI curriculums in professional education programs such as Commission on Accreditation of Medical Physics Education Programs (CAMPEP). Furthermore, we encourage experts from around the world in the field of AI, or RadOnc, or both, to take initiatives like McMedHacks to collaborate and push forward AI education in their departments and lead practical workshops, regardless of their levels of education.},
keywords = {},
pubstate = {published},
tppubtype = {award}
}
Purpose/Objective: The McMedHacks workshop and presentation series was created to teach individuals from various backgrounds about deep learning (DL) for medical image analysis in May, 2021. Material/Methods: McMedHacks is a free and student-led 8-week summer program. Registration for the event was open to everyone, including a form to survey participants’ area of expertise, country of origin, level of study, and level of programming skills. The weekly workshops were instructed by 8 students and experts assisted by 20 mentors who provided weekly tutorials. Recent developments in DL and medical physics were highlighted by 21 leaders from industry and academia. A virtual grand challenge Hackathon took place at the end of the workshop series. All events were held virtually and recorded on Zoom to accommodate all time zones and locations. The workshops were designed as interactive coding demos and shared through Google Colab notebooks. Results: McMedHacks gained 356 registrations from participants of 38 different countries (Fig. 1) from undergraduates, to PhDs and MDs. A vast number of disciplines and professions were represented, dominated by medical physics students, academic, and clinical medical physicists (Fig. 2). Sixty-nine participants earned a certificate of completion by having engaged with at least 12 of all 14 events. The program received participant feedback average scores of 4.768, 4.478, 4.579, 4.292, 4.84 out of five for the qualities of presentation, workshop session, tutorial and mentor, assignments, and course delivery, respectively. The eight-week long workshop’s duration allowed participants to digest the taught materials in a continuous manner as opposed to bootcamp-style conference workshops. Conclusion: The overwhelming interest and engagement for the McMedHacks workshop series from the Radiation Oncology (RadOnc) community illustrates a demand for Artificial Intelligence (AI) education in RadOnc. The future of RadOnc clinics will inevitably integrate AI. Therefore, current RadOnc professionals, and student and resident trainees should be prepared to understand basic AI principles and its applications to troubleshoot, innovate, and collaborate. McMedHacks set an excellent example of promoting open and multidisciplinary education, scientific communication, and leadership for integrating AI education into the RadOnc community on an international level. Therefore, we advocate for implementation of AI curriculums in professional education programs such as Commission on Accreditation of Medical Physics Education Programs (CAMPEP). Furthermore, we encourage experts from around the world in the field of AI, or RadOnc, or both, to take initiatives like McMedHacks to collaborate and push forward AI education in their departments and lead practical workshops, regardless of their levels of education.
Biological & Biomedical Engineering PhD Recruitment Award award
2022, (These awards are designed to help recruit top students to our program and are offered to applicants wishing to start in Fall or Winter. The standard recruitment awards are $10,000/year for three years for Doctoral students.).
@award{nokey,
title = {Biological & Biomedical Engineering PhD Recruitment Award },
author = {Yujing Zou},
url = {https://www.mcgill.ca/bbme/programs/funding#BME-Recruitment-Award},
year = {2022},
date = {2022-05-10},
urldate = {2022-05-10},
organization = {McGill Biological & Biomedical Engineering department },
note = {These awards are designed to help recruit top students to our program and are offered to applicants wishing to start in Fall or Winter. The standard recruitment awards are $10,000/year for three years for Doctoral students.},
keywords = {},
pubstate = {published},
tppubtype = {award}
}
Biological & Biomedical Engineering PhD Recruitment Award award
2022.
@award{nokey,
title = {Biological & Biomedical Engineering PhD Recruitment Award },
author = {Hossein Jafarzadeh },
url = {https://www.mcgill.ca/bbme/programs/funding#BME-Recruitment-Award},
year = {2022},
date = {2022-05-10},
keywords = {},
pubstate = {published},
tppubtype = {award}
}
Graduate Research Enhancement and Travel Awards (GREAT Awards) award
2022, (In 2009, Graduate and Postdoctoral Studies introduced the Graduate Research Enhancement and Travel awards (GREAT awards) program in consultation with the Faculty Deans and Associate Deans. These awards cover dissemination of research through graduate student presentations at conferences, and other graduate student research-enhancement activities, such as travel for fieldwork, archival inquiry and extra-mural collaborative research. GREAT budgets are allocated to Faculties each year, and as such, are managed directly by the Associate Dean’s office.).
@award{nokey,
title = {Graduate Research Enhancement and Travel Awards (GREAT Awards)},
author = {Yujing Zou},
url = {https://www.mcgill.ca/gps/funding/fac-staff/awards/great},
year = {2022},
date = {2022-04-14},
note = {In 2009, Graduate and Postdoctoral Studies introduced the Graduate Research Enhancement and Travel awards (GREAT awards) program in consultation with the Faculty Deans and Associate Deans. These awards cover dissemination of research through graduate student presentations at conferences, and other graduate student research-enhancement activities, such as travel for fieldwork, archival inquiry and extra-mural collaborative research. GREAT budgets are allocated to Faculties each year, and as such, are managed directly by the Associate Dean's office.},
keywords = {},
pubstate = {published},
tppubtype = {award}
}
Second prize at the International Conference on Monte Carlo Techniques for Medical Applications award
2022.
@award{nokey,
title = {Second prize at the International Conference on Monte Carlo Techniques for Medical Applications },
author = {Liam Carroll and Shirin A. Enger},
year = {2022},
date = {2022-04-13},
urldate = {2022-04-13},
journal = {International Conference on Monte Carlo Techniques for Medical Applications },
abstract = {Introduction
Geant4[1] is a Monte Carlo toolkit that provides a flexible platform to design radiation transport simulations. This flexibility requires a high level of complexity when writing new user-codes. New users must undergo extensive training to begin writing useful simulations. The aim of this study was to develop a modular radiation simulation software package called MaRSS based on Geant4 user-code to serve as both an educational tool and as a simulation tool for medical radiation detector simulations.
Materials & Methods
MaRSS builds on Geant4 using Penelope electromagnetic physics models and cross-sections[2]. To give the users possibility to change simulation parameters without changing the source code, MaRSS is equipped with a set of messenger classes which are intercom modules provided by Geant4 to configure applications and provide user interactivity with the code. These messenger classes add additional user commands that can be used to add or remove volumes from the simulation geometry and associated sensitive detectors. The sensitive detectors are objects that Geant4 uses to save simulation results. A number of default volumes and detectors are included in MaRSS that can be used for the design of scintillating fiber-based radiation detectors. MaRSS adds to the existing Geant4 sensitive detector code by creating a new base class called RunSD that is inherited by all sensitive detector objects. RunSD is implemented such that the code needed to initialize a sensitive detector is included in two classes, normally, this code is spread out in several classes. A similar approach is taken with geometrical volumes. To validate MaRSS, range in water of positrons emitted from four radioisotopes commonly used for positron emission tomography was calculated and compared with published work: Fluorine-18 (18F), Carbon-11 (11C), Oxygen-15 (15O) and Gallium-68 (68Ga). A sphere with a radius of 1 m was filed with water. For each radioisotope, 100 million decay events were simulated originating at the center of the simulated water sphere. The resulting positrons were allowed to annihilate. Two energy cuts were simulated, 1 keV and 0.1 keV. Two histograms were created, one using the annihilation locations and another with the energy of the emitted positrons. Results were compared with published positron range values calculated with a PENELOPE[2]-based Monte Carlo software called PeneloPET [3], an analytical expression to estimate the range of positrons described by Cal-Gonzales et.al.[3], a simulation by Lehnert et. al. [4] written using GATE[5] and a separate Monte Carlo software written by Champion and Le Loirec[6] that directly simulates the formation of positronium in water to calculate positron range.
Results
Figure 1 shows the mean calculated positron ranges and calculated positron emission energies compared to literature values. Simulated positron energy means were within 1.8% of literature values. Simulated ranges were within 2% of GATE simulation[4].
References
[1] S. Agostinelli et al., “Geant4—a simulation toolkit,” Nucl. Instruments Methods Phys. Res. Sect. A Accel. Spectrometers, Detect. Assoc. Equip., vol. 506, no. 3, pp. 250–303, Jul. 2003.
[2] J. Baró, J. Sempau, J. M. Fernández-Varea, and F. Salvat, “PENELOPE: An algorithm for Monte Carlo simulation of the penetration and energy loss of electrons and positrons in matter,” Nucl. Inst. Methods Phys. Res. B, vol. 100, no. 1, pp. 31–46, May 1995.
[3] J. Cal-González et al., “Positron range estimations with PeneloPET,” Phys. Med. Biol., vol. 58, no. 15, pp. 5127–5152, 2013.
[4] W. Lehnert, M.-C. Gregoire, A. Reilhac, and S. R. Meikle, “Analytical positron range modelling in heterogeneous media for PET Monte Carlo simulation,” Phys. Med. Biol., vol. 56, no. 11, p. 3313, May 2011.
[5] D. Strul, G. Santin, D. Lazaro, V. Breton, and C. Morel, “GATE (geant4 application for tomographic emission): a PET/SPECT general-purpose simulation platform,” Nucl. Phys. B - Proc. Suppl., vol. 125, pp. 75–79, Sep. 2003.
[6] C. Champion and C. Le Loirec, “Positron follow-up in liquid water: II. Spatial and energetic study for the most important radioisotopes used in PET,” Phys. Med. Biol., vol. 52, no. 22, pp. 6605–6625, Nov. 2007.
},
keywords = {},
pubstate = {published},
tppubtype = {award}
}
Introduction
Geant4[1] is a Monte Carlo toolkit that provides a flexible platform to design radiation transport simulations. This flexibility requires a high level of complexity when writing new user-codes. New users must undergo extensive training to begin writing useful simulations. The aim of this study was to develop a modular radiation simulation software package called MaRSS based on Geant4 user-code to serve as both an educational tool and as a simulation tool for medical radiation detector simulations.
Materials & Methods
MaRSS builds on Geant4 using Penelope electromagnetic physics models and cross-sections[2]. To give the users possibility to change simulation parameters without changing the source code, MaRSS is equipped with a set of messenger classes which are intercom modules provided by Geant4 to configure applications and provide user interactivity with the code. These messenger classes add additional user commands that can be used to add or remove volumes from the simulation geometry and associated sensitive detectors. The sensitive detectors are objects that Geant4 uses to save simulation results. A number of default volumes and detectors are included in MaRSS that can be used for the design of scintillating fiber-based radiation detectors. MaRSS adds to the existing Geant4 sensitive detector code by creating a new base class called RunSD that is inherited by all sensitive detector objects. RunSD is implemented such that the code needed to initialize a sensitive detector is included in two classes, normally, this code is spread out in several classes. A similar approach is taken with geometrical volumes. To validate MaRSS, range in water of positrons emitted from four radioisotopes commonly used for positron emission tomography was calculated and compared with published work: Fluorine-18 (18F), Carbon-11 (11C), Oxygen-15 (15O) and Gallium-68 (68Ga). A sphere with a radius of 1 m was filed with water. For each radioisotope, 100 million decay events were simulated originating at the center of the simulated water sphere. The resulting positrons were allowed to annihilate. Two energy cuts were simulated, 1 keV and 0.1 keV. Two histograms were created, one using the annihilation locations and another with the energy of the emitted positrons. Results were compared with published positron range values calculated with a PENELOPE[2]-based Monte Carlo software called PeneloPET [3], an analytical expression to estimate the range of positrons described by Cal-Gonzales et.al.[3], a simulation by Lehnert et. al. [4] written using GATE[5] and a separate Monte Carlo software written by Champion and Le Loirec[6] that directly simulates the formation of positronium in water to calculate positron range.
Results
Figure 1 shows the mean calculated positron ranges and calculated positron emission energies compared to literature values. Simulated positron energy means were within 1.8% of literature values. Simulated ranges were within 2% of GATE simulation[4].
References
[1] S. Agostinelli et al., “Geant4—a simulation toolkit,” Nucl. Instruments Methods Phys. Res. Sect. A Accel. Spectrometers, Detect. Assoc. Equip., vol. 506, no. 3, pp. 250–303, Jul. 2003.
[2] J. Baró, J. Sempau, J. M. Fernández-Varea, and F. Salvat, “PENELOPE: An algorithm for Monte Carlo simulation of the penetration and energy loss of electrons and positrons in matter,” Nucl. Inst. Methods Phys. Res. B, vol. 100, no. 1, pp. 31–46, May 1995.
[3] J. Cal-González et al., “Positron range estimations with PeneloPET,” Phys. Med. Biol., vol. 58, no. 15, pp. 5127–5152, 2013.
[4] W. Lehnert, M.-C. Gregoire, A. Reilhac, and S. R. Meikle, “Analytical positron range modelling in heterogeneous media for PET Monte Carlo simulation,” Phys. Med. Biol., vol. 56, no. 11, p. 3313, May 2011.
[5] D. Strul, G. Santin, D. Lazaro, V. Breton, and C. Morel, “GATE (geant4 application for tomographic emission): a PET/SPECT general-purpose simulation platform,” Nucl. Phys. B – Proc. Suppl., vol. 125, pp. 75–79, Sep. 2003.
[6] C. Champion and C. Le Loirec, “Positron follow-up in liquid water: II. Spatial and energetic study for the most important radioisotopes used in PET,” Phys. Med. Biol., vol. 52, no. 22, pp. 6605–6625, Nov. 2007.
Geant4[1] is a Monte Carlo toolkit that provides a flexible platform to design radiation transport simulations. This flexibility requires a high level of complexity when writing new user-codes. New users must undergo extensive training to begin writing useful simulations. The aim of this study was to develop a modular radiation simulation software package called MaRSS based on Geant4 user-code to serve as both an educational tool and as a simulation tool for medical radiation detector simulations.
Materials & Methods
MaRSS builds on Geant4 using Penelope electromagnetic physics models and cross-sections[2]. To give the users possibility to change simulation parameters without changing the source code, MaRSS is equipped with a set of messenger classes which are intercom modules provided by Geant4 to configure applications and provide user interactivity with the code. These messenger classes add additional user commands that can be used to add or remove volumes from the simulation geometry and associated sensitive detectors. The sensitive detectors are objects that Geant4 uses to save simulation results. A number of default volumes and detectors are included in MaRSS that can be used for the design of scintillating fiber-based radiation detectors. MaRSS adds to the existing Geant4 sensitive detector code by creating a new base class called RunSD that is inherited by all sensitive detector objects. RunSD is implemented such that the code needed to initialize a sensitive detector is included in two classes, normally, this code is spread out in several classes. A similar approach is taken with geometrical volumes. To validate MaRSS, range in water of positrons emitted from four radioisotopes commonly used for positron emission tomography was calculated and compared with published work: Fluorine-18 (18F), Carbon-11 (11C), Oxygen-15 (15O) and Gallium-68 (68Ga). A sphere with a radius of 1 m was filed with water. For each radioisotope, 100 million decay events were simulated originating at the center of the simulated water sphere. The resulting positrons were allowed to annihilate. Two energy cuts were simulated, 1 keV and 0.1 keV. Two histograms were created, one using the annihilation locations and another with the energy of the emitted positrons. Results were compared with published positron range values calculated with a PENELOPE[2]-based Monte Carlo software called PeneloPET [3], an analytical expression to estimate the range of positrons described by Cal-Gonzales et.al.[3], a simulation by Lehnert et. al. [4] written using GATE[5] and a separate Monte Carlo software written by Champion and Le Loirec[6] that directly simulates the formation of positronium in water to calculate positron range.
Results
Figure 1 shows the mean calculated positron ranges and calculated positron emission energies compared to literature values. Simulated positron energy means were within 1.8% of literature values. Simulated ranges were within 2% of GATE simulation[4].
References
[1] S. Agostinelli et al., “Geant4—a simulation toolkit,” Nucl. Instruments Methods Phys. Res. Sect. A Accel. Spectrometers, Detect. Assoc. Equip., vol. 506, no. 3, pp. 250–303, Jul. 2003.
[2] J. Baró, J. Sempau, J. M. Fernández-Varea, and F. Salvat, “PENELOPE: An algorithm for Monte Carlo simulation of the penetration and energy loss of electrons and positrons in matter,” Nucl. Inst. Methods Phys. Res. B, vol. 100, no. 1, pp. 31–46, May 1995.
[3] J. Cal-González et al., “Positron range estimations with PeneloPET,” Phys. Med. Biol., vol. 58, no. 15, pp. 5127–5152, 2013.
[4] W. Lehnert, M.-C. Gregoire, A. Reilhac, and S. R. Meikle, “Analytical positron range modelling in heterogeneous media for PET Monte Carlo simulation,” Phys. Med. Biol., vol. 56, no. 11, p. 3313, May 2011.
[5] D. Strul, G. Santin, D. Lazaro, V. Breton, and C. Morel, “GATE (geant4 application for tomographic emission): a PET/SPECT general-purpose simulation platform,” Nucl. Phys. B – Proc. Suppl., vol. 125, pp. 75–79, Sep. 2003.
[6] C. Champion and C. Le Loirec, “Positron follow-up in liquid water: II. Spatial and energetic study for the most important radioisotopes used in PET,” Phys. Med. Biol., vol. 52, no. 22, pp. 6605–6625, Nov. 2007.
2021
T I Gurman Prize in Physics award
2021.
@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.
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}
}
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}
}
Merit-based recruitment award for first year MSc students. award
2021.
@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}
}
Mitacs Globalink Research Award award
2021.
@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.
2021.
@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/
2020
Graduate Excellence Fellowship award
2020.
@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}
}
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}
}
First prize for best presentation at the congrès annuel de l’AQPMC award
2020.
@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.
Math And Physics Class Of 1965 Prize award
2020.
@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.
Excellence Award from Department of Biological and Biomedical Engineering award
2020.
@award{Carroll2020,
title = {Excellence Award from Department of Biological and Biomedical Engineering},
author = {Liam Carroll},
year = {2020},
date = {2020-01-01},
urldate = {2020-01-01},
organization = {McGill University},
school = {Bioengineering and Biomedical Engineering Program},
abstract = {The award recognizes excellent performance in the PhD Program of the BBME/BME graduate program. The selection is based on a combination of overall excellence, performance in the program, grades, progress in project and publications. },
howpublished = {Department of Biological and Biomedical Engineering},
keywords = {award},
pubstate = {published},
tppubtype = {award}
}
The award recognizes excellent performance in the PhD Program of the BBME/BME graduate program. The selection is based on a combination of overall excellence, performance in the program, grades, progress in project and publications.
2019
Canada Research Chair Tier II in Medical Physics award
2019.
@award{Enger2019,
title = {Canada Research Chair Tier II in Medical Physics},
author = {Shirin A. Enger },
year = {2019},
date = {2019-10-01},
urldate = {2019-10-01},
organization = {Government of Canada},
keywords = {},
pubstate = {published},
tppubtype = {award}
}
Development of an in-vivo radiation dosimeter for radiotherapy. Winner of the best in Physics Award. award
2019.
@award{Mégrourèche2019,
title = {Development of an in-vivo radiation dosimeter for radiotherapy. Winner of the best in Physics Award.},
author = {Julien Mégrourèche and Lilian Childress and Jack Sankey and Alaina Bui and Shirin A. Enger},
year = {2019},
date = {2019-10-01},
urldate = {2019-10-01},
howpublished = {Radiation Association of Radiation Oncology (CARO)},
keywords = {award},
pubstate = {published},
tppubtype = {award}
}
Development of a hydrated electron dosimeter for in vivo applications in radiotherapy: A proof of concept. Winner of the J.R. Cunningham Young Investigators Award award
2019.
@award{Mégrourèche2019b,
title = {Development of a hydrated electron dosimeter for in vivo applications in radiotherapy: A proof of concept. Winner of the J.R. Cunningham Young Investigators Award},
author = {Julien Mégrourèche and Lilian Childress and Jack Sankey and Alaina Bui and Shirin A. Enger },
year = {2019},
date = {2019-09-01},
urldate = {2019-09-01},
howpublished = {Canadian Organization of Medical Physicists (COMP)},
keywords = {award},
pubstate = {published},
tppubtype = {award}
}
Winners of the Centech propulsion program award
2019.
@award{Carroll2019,
title = {Winners of the Centech propulsion program},
author = {Liam Carroll and Gustavo Kertzscher and Shirin A. Enger},
year = {2019},
date = {2019-01-01},
urldate = {2019-01-01},
organization = {Centech},
abstract = {Two years’ business incubator, (50 k CAD) + access to consulting firms to build a commercial version of BetaSense that can be used in a clinical environment for patient measurements. },
keywords = {award},
pubstate = {published},
tppubtype = {award}
}
Two years’ business incubator, (50 k CAD) + access to consulting firms to build a commercial version of BetaSense that can be used in a clinical environment for patient measurements.
Winners of the Marika Zelenka Roy Innovation Prize award
2019.
@award{Carroll2019b,
title = {Winners of the Marika Zelenka Roy Innovation Prize},
author = {Liam Carroll and Gustavo Kertzscher and Shirin A. Enger},
year = {2019},
date = {2019-01-01},
urldate = {2019-01-01},
organization = {McGill University},
abstract = {(50 k CAD) at McGill University Clinical Innovation Competition for the detector BetaSense (A non-invasive positron detector to measure the arterial input function for pharmacokinetic modelling in dynamic positron emission tomography imaging). },
howpublished = {McGill University Clinical Innovation Competition},
keywords = {award},
pubstate = {published},
tppubtype = {award}
}
(50 k CAD) at McGill University Clinical Innovation Competition for the detector BetaSense (A non-invasive positron detector to measure the arterial input function for pharmacokinetic modelling in dynamic positron emission tomography imaging).
Young Investigator Competition Award – Urethra-Sparing with Intensity Modulated Brachytherapy for Prostate Cancer award
2019.
@award{Famulari2019,
title = {Young Investigator Competition Award - Urethra-Sparing with Intensity Modulated Brachytherapy for Prostate Cancer},
author = {Gabriel Famulari and Shirin A. Enger},
year = {2019},
date = {2019-01-01},
urldate = {2019-01-01},
howpublished = {Curietherapies 2019},
keywords = {award},
pubstate = {published},
tppubtype = {award}
}
2nd prize in the Young Investigator Competition award
2019.
@award{Mégrourèche2019c,
title = {2nd prize in the Young Investigator Competition},
author = {Julien Mégrourèche and Alaina Bui and Jack Sankey and Lilian Childress and Shirin A. Enger},
year = {2019},
date = {2019-01-01},
urldate = {2019-01-01},
organization = {McGill University Health Center},
abstract = {Development of a Hydrated Electron Dosimeter for Radiotherapy
Applications: A Proof of Concept. 2nd prize in the Young Investigator Competition award at the Research Institute of McGill University Health Center, Cancer Research program.},
howpublished = {Research Institute of McGill University Health Center},
keywords = {award},
pubstate = {published},
tppubtype = {award}
}
Development of a Hydrated Electron Dosimeter for Radiotherapy
Applications: A Proof of Concept. 2nd prize in the Young Investigator Competition award at the Research Institute of McGill University Health Center, Cancer Research program.
Applications: A Proof of Concept. 2nd prize in the Young Investigator Competition award at the Research Institute of McGill University Health Center, Cancer Research program.
0000
[No title] award
0000.
@award{nokey,
title = {[No title]},
keywords = {},
pubstate = {published},
tppubtype = {award}
}