The goal of this project is to assess and improve our understanding of the magnitude and clinical impact of (a) assumptions and approximations of current proton therapy regarding the physical interactions of protons with patient anatomy and treatment devices, (b) the markedly different dose distribution patterns of protons and photons, and (c) the assumption of the variability of the relative biological effectiveness (RBE) of protons compared to the current practice of using a constant RBE of 1.1. This goal will be accomplished partly through the analyses of clinical data (local control, toxicities and imaged response) from the P01 clinical trials and partly through computer simulations and through in-vivo experiments. Achieving this goal is of high significance in that the knowledge gained about the factors affecting treatment response (e.g., inter- and intra-fractional anatomic variations, approximations in predicting physical dose, RBE variability, etc.) would be critical for making reliable treatment decisions about the appropriateness of proton therapy, for correctly evaluating the clinical effectiveness of planned proton dose distributions, and for developing advanced methods to design optimum and robust IMPT to exploit the full potential of proton therapy. This project supports the mission of the NCI to improve the treatment and continuing care of cancer patients.
This research aims to improve radiation treatment for cancer patients by improving our ability to direct the radiation at the tumor to spare adjacent normal tissue by using protons (charged particles) with intensity- modulated proton therapy. This can potentially improve cancer cure rates, reduce side effects, or both, depending on the clinical scenario. With an increasing number of proton centers in the United States and abroad the research in this program project is increasingly important for public health.
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|Guan, Fada; Geng, Changran; Ma, Duo et al. (2018) RBE Model-Based Biological Dose Optimization for Proton Radiobiology Studies. Int J Part Ther 5:160-171|
|Liao, Zhongxing; Simone 2nd, Charles B (2018) Particle therapy in non-small cell lung cancer. Transl Lung Cancer Res 7:141-152|
|Blanchard, Pierre; Gunn, Gary Brandon; Lin, Alexander et al. (2018) Proton Therapy for Head and Neck Cancers. Semin Radiat Oncol 28:53-63|
|Chen, Yizheng; Grassberger, Clemens; Li, Junli et al. (2018) Impact of potentially variable RBE in liver proton therapy. Phys Med Biol 63:195001|
|Geng, Changran; Gates, Drake; Bronk, Lawrence et al. (2018) Physical parameter optimization scheme for radiobiological studies of charged particle therapy. Phys Med 51:13-21|
|Liao, Zhongxing; Lee, J Jack; Komaki, Ritsuko et al. (2018) Bayesian Adaptive Randomization Trial of Passive Scattering Proton Therapy and Intensity-Modulated Photon Radiotherapy for Locally Advanced Non-Small-Cell Lung Cancer. J Clin Oncol 36:1813-1822|
|Yepes, Pablo; Adair, Antony; Grosshans, David et al. (2018) Comparison of Monte Carlo and analytical dose computations for intensity modulated proton therapy. Phys Med Biol 63:045003|
|Unkelbach, Jan; Paganetti, Harald (2018) Robust Proton Treatment Planning: Physical and Biological Optimization. Semin Radiat Oncol 28:88-96|
|Vassiliev, Oleg N; Kry, Stephen F; Grosshans, David R et al. (2018) Average stopping powers for electron and photon sources for radiobiological modeling and microdosimetric applications. Phys Med Biol 63:055007|
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