Reply to Comments on 'Modeling for predicting survival fraction of cells after ultra-high dose rate irradiation'.

IF 3.4 3区 医学 Q2 ENGINEERING, BIOMEDICAL Physics in medicine and biology Pub Date : 2024-12-12 DOI:10.1088/1361-6560/ad997d
Yuta Shiraishi, Yusuke Matsuya, Hisanori Fukunaga
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Abstract

Liew and Mairani (2024Phys. Med. Biol.69248001) commented on our previous reply to comments on our paper, 'Modeling for predicting survival fraction of cells after ultra-high dose rate irradiation'. We appreciate their comments on the choice of experimental data on DNA damage for cell survival and agree that the estimate of the dose-response curve on cell survival depends on the selection of DNA damage data. As an additional benchmark test, we compared the relative biological effectiveness (RBE) predicted using the recommended DNA damage data measured in normoxia with those reported in our original paper, and confirmed that the difference in RBE was less than 8%. Although our model allows for the estimation of cell survival and RBE under ultra-high dose rate (UHDR) irradiation, we highlight that a further accumulation of experimental data on DNA damage under UHDR irradiation is necessary for the further development of biophysical models concerning the mechanistical estimation of biological effects.

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回复关于“超高剂量率辐照后细胞存活率预测模型”的评论。
刘和迈拉尼(2009);Med. Biol.69248001)评论了我们之前对论文评论的回复,“超高剂量率辐照后预测细胞存活比例的建模”。我们赞赏他们对选择DNA损伤对细胞存活的实验数据的评论,并同意细胞存活的剂量-反应曲线的估计取决于DNA损伤数据的选择。作为额外的基准测试,我们比较了使用推荐的DNA损伤数据预测的相对生物有效性(RBE)与我们原始论文中报道的结果,并确认RBE的差异小于8%。虽然我们的模型允许估计超高剂量率(UHDR)照射下的细胞存活和RBE,但我们强调,进一步积累超高剂量率照射下DNA损伤的实验数据对于进一步发展有关生物效应的机械估计的生物物理模型是必要的。
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来源期刊
Physics in medicine and biology
Physics in medicine and biology 医学-工程:生物医学
CiteScore
6.50
自引率
14.30%
发文量
409
审稿时长
2 months
期刊介绍: The development and application of theoretical, computational and experimental physics to medicine, physiology and biology. Topics covered are: therapy physics (including ionizing and non-ionizing radiation); biomedical imaging (e.g. x-ray, magnetic resonance, ultrasound, optical and nuclear imaging); image-guided interventions; image reconstruction and analysis (including kinetic modelling); artificial intelligence in biomedical physics and analysis; nanoparticles in imaging and therapy; radiobiology; radiation protection and patient dose monitoring; radiation dosimetry
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