Reference dosimetry for MRI-Linacs: an addendum to the 2020 IPEM code of practice for high-energy photon therapy dosimetry.

IF 3.3 3区 医学 Q2 ENGINEERING, BIOMEDICAL
Ilias Billas, Geoff J Budgell, Ben George, Russell A S Thomas, Simon Duane, David J Eaton
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引用次数: 0

Abstract

The 2020 Institute of Physics and Engineering in Medicine code of practice (COP) for megavoltage dosimetry (Eaton et al 2020, Phys. Med. Biol. 65(19): 195006) provides standardised and practical methods for measurement of absorbed dose to water, linked to calibration by the National Physical Laboratory. This report extends the use of that COP to MRI-Linacs through the addition of two correction factors: (1) to account for the influence of the magnetic field on the absorbed dose and model-specific chamber response; and (2) to account for differences in chamber response in the beam spectrum of the MRI-Linac and the Linac where the cross-calibration is performed. Guidance is provided on practical aspects of chamber calibration and dose measurement in MRI-Linac beams, including the use of liquid water, consistent chamber orientation and corrections for other influence quantities. Using this approach uncertainties are similar to other applications of the COP.

MRI-Linacs 参考剂量测定:2020 年 IPEM 高能光子治疗剂量测定实践准则增编。
2020 年物理与工程医学研究所巨电压剂量测定实践准则(COP)(Eaton 等,2020 年,Phys. Med.65(19):195006)提供了测量水吸收剂量的标准化实用方法,并与国家物理实验室的校准联系在一起。本报告通过增加两个校正因子,将该 COP 的使用扩展到 MRI-Linacs 上:(1) 考虑到磁场对吸收剂量和特定型号腔室响应的影响;(2) 考虑到核磁共振成像-直子加速器和进行交叉校准的直子加速器的束谱中腔室响应的差异。就 MRI-Linac 射束中的腔室校准和剂量测量的实际方面提供了指导,包括液态水的使用、一致的腔室方向和其他影响量的校正。使用这种方法的不确定性与 COP 的其他应用类似。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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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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