University of California San Francisco, Department of Radiation Oncology 1600 Divisadero Street, San Francisco, CA 94143 United States of America.
Loma Linda University School of Medicine, 11175 Campus St, Loma Linda, CA 92350, United States of America.
Phys Med Biol. 2023 Aug 14;68(17). doi: 10.1088/1361-6560/acea16.
. To propose a mathematical model for applying ionization detail (ID), the detailed spatial distribution of ionization along a particle track, to proton and ion beam radiotherapy treatment planning (RTP).. Our model provides for selection of preferred ID parameters () for RTP, that associate closest to biological effects. Cluster dose is proposed to bridge the large gap between nanoscopicand macroscopic RTP. Selection ofis demonstrated using published cell survival measurements for protons through argon, comparing results for nineteen:,= 2, 3, …, 10, the number of ionizations in clusters ofor more per particle, and,= 1, 2, …, 10, the number of clusters ofor more per particle. We then describe application of the model to ID-based RTP and propose a path to clinical translation.. The preferredwereandfor aerobic cells,andfor hypoxic cells. Significant differences were found in cell survival for beams having the same LET or the preferred. Conversely, there was no significant difference forfor aerobic cells andfor hypoxic cells, regardless of ion beam atomic number or energy. Further, cells irradiated with the same cluster dose for thesehad the same cell survival. Based on these preliminary results and other compelling results in nanodosimetry, it is reasonable to assert thatexist that are more closely associated with biological effects than current LET-based approaches and microdosimetric RBE-based models used in particle RTP. However, more biological variables such as cell line and cycle phase, as well as ion beam pulse structure and rate still need investigation.. Our model provides a practical means to select preferredfrom radiobiological data, and to convertto the macroscopic cluster dose for particle RTP.
. 提出了一种应用离子化细节(ID)的数学模型,即沿着粒子轨迹的详细空间分布的离子化,用于质子和离子束放射治疗计划(RTP)。.. 我们的模型提供了选择最适合 RTP 的 ID 参数()的方法,这些参数与生物学效应最相关。簇剂量被提议用于弥合微观和宏观 RTP 之间的巨大差距。选择是使用已发表的质子穿过氩的细胞存活测量来证明的,比较了十九个结果:,= 2, 3, …, 10,每个粒子中或更多个离子化簇的数量,和,= 1, 2, …, 10,每个粒子中或更多个簇的数量。然后,我们描述了该模型在基于 ID 的 RTP 中的应用,并提出了向临床转化的途径。.. 对于有氧细胞,优选的和分别为和;对于缺氧细胞,优选的和分别为和。对于具有相同 LET 或优选的离子束,细胞存活存在显著差异。相反,对于有氧细胞和缺氧细胞,和没有显著差异,无论离子束原子数或能量如何。此外,对于这些,具有相同簇剂量的细胞具有相同的细胞存活率。基于这些初步结果和纳米剂量学中的其他有说服力的结果,可以合理地断言,存在与生物学效应更相关的,而不是当前基于 LET 的方法和用于粒子 RTP 的微剂量 RBE 模型。然而,还需要更多的生物学变量,如细胞系和周期阶段,以及离子束脉冲结构和速率进行研究。.. 我们的模型为从放射生物学数据中选择优选的提供了一种实用的方法,并将转换为用于粒子 RTP 的宏观簇剂量。