As proton therapy has joined the mainstream of radiation treatment, Monte Carlo simulation (MC) has been the research engine driving highly accurate dose delivery. The TOPAS Tool for Particle Simulation, developed in the previous funding cycle, makes MC accessible as never before. As radiation therapy pushes to the next challenge, where physics and biology come together, TOPAS will bridge the divide between these two research domains. TOPAS can track any kind of particle through any kind of treatment head, import a patient geometry, score dose, fluence, etc., has advanced graphics and scoring features, and is fully four-dimensional to handle all time-dependent aspects of a simulation. Research physicists use TOPAS to improve proton delivery systems towards safer and more effective treatments, easily setting up and running complex MC simulations that used to take MC specialists months to prepare. Clinical physicists use TOPAS to optimize the therapeutic ratio, simulating patient- specific treatment plans with the full accuracy of MC at the touch of a button. We will bring the same benefits to the radiobiological community. Where radiobiology research has previously suffered from insufficient interdisciplinary collaboration between physicists and biologists, TOPAS will bridge the gap. TOPAS will let biologists study detailed physics aspects of their experiments and let physicists employ the latest radiobiology results in the clinic. TOPAS will provide a common research platform to proton therapy facilities, biology laboratories and universities.
Specific Aim 1 : Expand TOPAS to facilitate research on organ effect biology a. Provide a framework for tumor and normal tissue outcome modeling b. Validate by reproducing published data on proton beam normal tissue complications Specific Aim 2: Expand TOPAS to facilitate research on cellular effect biology a. Provide a framework for cellular effect RBE modeling b. Validate by calculating the relative biological effectiveness f proton beams Specific Aim 3: Expand TOPAS to facilitate research on sub-cellular effect biology a. Provide a framework for sub-cellular effect mechanistic modeling b. Validate by reproducing data on ionization frequencies and DNA damage Specific Aim 4: Support and share TOPAS for all user communities a. Support current TOPAS user communities in proton therapy physics b. Reach out to new user communities in other therapy modalities and imaging c. Continuing software innovation, enhanced graphical user interfaces and beyond

Public Health Relevance

Medical physics is reaching the boundary where further improvements require connecting the physics to the underlying biology. In particular, in proton therapy there are several controversies related to biological effects that need to be studied experimentally and theoretically. This application will extend the TOPAS functionality into the regime of chemical processes and biological modeling. This expansion will make Monte Carlo particle transport techniques as available to the biologist as TOPAS has already made them available to the medical physicist. We envisage that TOPAS will become the preferred platform for both physics and biology research in proton therapy. Our new proposal focus is on all three domains of radiation biology modeling; i.e. organ effects (outcome), cellular effects (RBE) and sub-cellular (mechanistic) effects. Currently there is no single application that covers the whole spectrum from organ to sub-cellular biology.

National Institute of Health (NIH)
National Cancer Institute (NCI)
Research Project (R01)
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Special Emphasis Panel (ZRG1-OTC-K (04))
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Capala, Jacek
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Massachusetts General Hospital
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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
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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

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