Academic literature on the topic 'Rs of radiobiology'
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Journal articles on the topic "Rs of radiobiology":
Roberts, C., and C. Paterson. "An Exploration of the Rs of Radiobiology in Prostate Cancer." Seminars in Oncology Nursing 36, no. 4 (August 2020): 151054. http://dx.doi.org/10.1016/j.soncn.2020.151054.
Joiner, M. "SP-0663 The 4 Rs of radiobiology revisited in hypofractionated radiotherapy." Radiotherapy and Oncology 161 (August 2021): S533—S534. http://dx.doi.org/10.1016/s0167-8140(21)08647-3.
Brown, J. Martin, David J. Carlson, and David J. Brenner. "The Tumor Radiobiology of SRS and SBRT: Are More Than the 5 Rs Involved?" International Journal of Radiation Oncology*Biology*Physics 88, no. 2 (February 2014): 254–62. http://dx.doi.org/10.1016/j.ijrobp.2013.07.022.
Wannouss, M., V. D. Semel, G. G. Golyshev, and A. N. Goltsov. "Method for Determining Radioresistance of Cancer Cell Lines Based on Cluster Analysis of Clonogenic Cell Survival Data." Meditsinskaya Fizika, no. 1 (April 25, 2024): 18–35. http://dx.doi.org/10.52775/1810-200x-2024-101-1-18-35.
Dissertations / Theses on the topic "Rs of radiobiology":
Hami, Abdoul-Azize Rihab. "Simulation des processus radiobiologiques basés sur l'imagerie pour l'évaluation de schémas thérapeutiques individualisés en radiothérapie." Electronic Thesis or Diss., Brest, 2024. http://www.theses.fr/2024BRES0002.
Radiotherapy is one of the principal cancer treatments. Despite its intensive use in clinical practice, itseffectiveness depends on several factors. Several studies showed that the tumor response to radiotherapy differ from one patient to another. The response of tumor is influenced by several factors like hypoxia and multiple interactions between the tumor microenvironment and healthy cells. Five major biologic concepts called “5 Rs” resume these interactions. These concepts include reoxygenation, DNA damage-repair, cell cycle redistribution, cellular radiosensitivity and cellular repopulation.The optimal treatment strategy must consider these “5 Rs". In this study, we proposed as a first an approach to oxygenation modeling that can be considered as an optimization process in the absence of data concerning oxygen. We used a multi-scale model to predict the effects of radiotherapy on tumor growth based on information extracted from positron-emission tomography (PET) images. Then, we included to our model the ‘’5 Rs’’ of radiotherapy, to predict the effects of radiation on tumor growth. Finally, we presented a study of the effect of different types of fractionations on tumor response to radiotherapy