Proton therapy is one of the best methods available for treating cancer. While the value of Monte Carlo (MC) simulation for proton therapy is well established, there exists no software that combines ease-of-use with the level of flexibility needed for demanding clinical and research applications. The release of the BEAM/DOSXYZ MC in 1995 effectively addressed a similar barrier for conventional therapy, releasing a flood of valuable research projects and clinical applications, but this application does not work for proton therapy. A fast, easy-to-use """"""""BEAM/DOSXYZ for Protons"""""""" or """"""""PBeam"""""""" will unlock great potential for MC in proton therapy. It will enable researchers and clinical physicists to accurately determine dosimetric and radiobiological aspects of proton beams for individual patients, accelerate design of new proton treatment planning and delivery systems, facilitate design of detectors for dose measurement and imaging devices for image- guided radiotherapy, and provide clinicians with the capability to exploit the power of MC simulation in clinical practice, including the creation of treatment plans for individual patients with the accuracy and functionality required to optimize treatment. We will provide PBeam free of charge, for all common operating systems, with online training materials, minimizing barriers to use.

Public Health Relevance

While the value of Monte Carlo simulation for proton therapy is well established, there exists no software for this purpose that combines ease-of-use with the level of flexibility needed for demanding clinical and research applications. Consequently, this valuable calculation technique remains underutilized, difficult to apply and restricted to use by highly experienced software experts. With today's climate of increasing numbers of proton facilities and proton-related research, a fast and easy-to-use """"""""PBeam"""""""" will unlock great potential for Monte Carlo in proton therapy, helping researchers study dosimetric and radiobiological aspects of proton beams, helping them improve proton delivery, treatment planning and validation and helping clinicians exploit the power of Monte Carlo simulation in routine clinical practice.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Research Project (R01)
Project #
5R01CA140735-03
Application #
8074574
Study Section
Radiation Therapeutics and Biology Study Section (RTB)
Program Officer
Deye, James
Project Start
2009-07-01
Project End
2013-05-31
Budget Start
2011-06-01
Budget End
2012-05-31
Support Year
3
Fiscal Year
2011
Total Cost
$432,162
Indirect Cost
Name
Massachusetts General Hospital
Department
Type
DUNS #
073130411
City
Boston
State
MA
Country
United States
Zip Code
02199
Polster, Lisa; Schuemann, Jan; Rinaldi, Ilaria et al. (2015) Extension of TOPAS for the simulation of proton radiation effects considering molecular and cellular endpoints. Phys Med Biol 60:5053-70
Faddegon, Bruce A; Shin, Jungwook; Castenada, Carlos M et al. (2015) Experimental depth dose curves of a 67.5 MeV proton beam for benchmarking and validation of Monte Carlo simulation. Med Phys 42:4199-210
McNamara, Aimee L; Schuemann, Jan; Paganetti, Harald (2015) A phenomenological relative biological effectiveness (RBE) model for proton therapy based on all published in vitro cell survival data. Phys Med Biol 60:8399-416
Ramos-Méndez, J; Perl, J; Schümann, J et al. (2015) A framework for implementation of organ effect models in TOPAS with benchmarks extended to proton therapy. Phys Med Biol 60:5037-52
Méndez, J Ramos; Perl, J; Schümann, J et al. (2015) Improved efficiency in Monte Carlo simulation for passive-scattering proton therapy. Phys Med Biol 60:5019-35
Testa, Mauro; Min, Chul Hee; Verburg, Joost M et al. (2014) Range verification of passively scattered proton beams based on prompt gamma time patterns. Phys Med Biol 59:4181-95
Dowdell, S; Grassberger, C; Sharp, G C et al. (2013) Interplay effects in proton scanning for lung: a 4D Monte Carlo study assessing the impact of tumor and beam delivery parameters. Phys Med Biol 58:4137-56
Ramos-Méndez, José; Perl, Joseph; Faddegon, Bruce et al. (2013) Geometrical splitting technique to improve the computational efficiency in Monte Carlo calculations for proton therapy. Med Phys 40:041718
Grassberger, Clemens; Dowdell, Stephen; Lomax, Antony et al. (2013) Motion interplay as a function of patient parameters and spot size in spot scanning proton therapy for lung cancer. Int J Radiat Oncol Biol Phys 86:380-6
Testa, M; Schümann, J; Lu, H-M et al. (2013) Experimental validation of the TOPAS Monte Carlo system for passive scattering proton therapy. Med Phys 40:121719

Showing the most recent 10 out of 17 publications