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• W2609085856 abstract "Radiotherapy treatments to local tumors are always associated with dose deposit in surrounding tissues and even in distant tissues not traversed by the radiation beams. In the present work, we demonstrate by Monte Carlo simulations the impact of radiation energy on absorbed dose in a lung tumor and in other secondary organs in a digital mouse. We also report the energy difference between simulations of monoenergetic and spectral radiations, and between CT-based and atlas-made digital mouse.We simulated seven monoenergetic and spectral radiation beams from 50keV (or kVp) to 450keV (or kVp). For each energy mode, the beams were generated along seven angles converging on the tumor. We assessed the absorbed dose in ten volumes including the lungs, the heart and the spine.The results showed an increase of absorbed dose as a function of energy with a lowest dose at 100keV. In the secondary organs not traversed by the beams, the spinal cord received doses of 0.78% and 0.07%, and the spinal bone received 2.36% and 0.35% relative to those in the tumor, respectively at 50keV and at 450keV. A region in the heart not traversed by the beams received 2% of the dose to the tumor.The optimal energy to the tumor with relatively reduced doses to other organs was achieved at energies around 200keV. At these energies, the surrounding of the tumor received lesser doses. Monoenergetic radiations were found to be more appropriate to target the tumor than spectral radiations produced by X-ray tubes, and CT-based digital mouse was more realistic than atlas-based mouse since it accounts for tissue heterogeneity." @default.
• W2609085856 created "2017-05-05" @default.
• W2609085856 creator A5021066693 @default.
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• W2609085856 date "2017-05-01" @default.
• W2609085856 modified "2023-10-16" @default.
• W2609085856 title "Impact of X-ray energy on absorbed dose assessed with Monte Carlo simulations in a mouse tumor and in nearest organs irradiated with kilovoltage X-ray beams" @default.
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• W2609085856 doi "https://doi.org/10.1016/j.canrad.2017.01.008" @default.
• W2609085856 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/28461030" @default.
• W2609085856 hasPublicationYear "2017" @default.
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