Monte Carlo simulations in radiotherapy dosimetry.

Monte Carlo simulations in radiotherapy dosimetry.
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DOI:
10.1186/s13014-018-1065-3
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发表时间:
2018-06-27
期刊:
Radiation oncology (London, England)
影响因子:
--
通讯作者:
Andreo P
Andreo P
中科院分区:
其他
文献类型:
--
作者:
Andreo P

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蒙特卡罗(MC)方法在放射剂量测定中的应用在近几十年来几乎呈指数增长。它在该领域的广泛应用使这种计算机模拟技术成为参考和治疗计划剂量学计算的通用工具。这项工作回顾了不同的MC计算对剂量量,如停止功率比和摄动校正因子所需的参考电离室剂量,以及完全真实的MC模拟目前可用于临床加速器,探测器和病人治疗计划。提出的问题包括在参考剂量学中整个剂量学链中数据一致性的必要性,以及Bragg-Gray理论如何在小光子场中崩溃。这两个方面对MC治疗计划的应用都不太重要,但有重要的限制,如组织表征及其患者对患者的可变性,以及剂量对水和剂量对组织之间的转换,进行了详细的分析。尽管这些约束是不同类型治疗计划系统中使用的所有方法和算法所共有的,但它们使得MC治疗计划中涉及的不确定性仍然保持“不确定性”。
The use of the Monte Carlo (MC) method in radiotherapy dosimetry has increased almost exponentially in the last decades. Its widespread use in the field has converted this computer simulation technique in a common tool for reference and treatment planning dosimetry calculations. This work reviews the different MC calculations made on dosimetric quantities, like stopping-power ratios and perturbation correction factors required for reference ionization chamber dosimetry, as well as the fully realistic MC simulations currently available on clinical accelerators, detectors and patient treatment planning. Issues are raised that include the necessity for consistency in the data throughout the entire dosimetry chain in reference dosimetry, and how Bragg-Gray theory breaks down for small photon fields. Both aspects are less critical for MC treatment planning applications, but there are important constraints like tissue characterization and its patient-to-patient variability, which together with the conversion between dose-to-water and dose-to-tissue, are analysed in detail. Although these constraints are common to all methods and algorithms used in different types of treatment planning systems, they make uncertainties involved in MC treatment planning to still remain “uncertain”.
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