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混合剂量计算:一种用于微束放射治疗的剂量计算算法。

Hybrid dose calculation: a dose calculation algorithm for microbeam radiation therapy.

机构信息

The European Synchrotron Radiation Facility, 71 Avenue des Martyrs 38000, Grenoble, France. The Institute of Cancer Research, 15 Cotswold Road, Sutton, London SM2 5NG, United Kingdom. Author to whom any correspondence should be addressed.

出版信息

Phys Med Biol. 2018 Feb 13;63(4):045013. doi: 10.1088/1361-6560/aaa705.

Abstract

Microbeam radiation therapy (MRT) is still a preclinical approach in radiation oncology that uses planar micrometre wide beamlets with extremely high peak doses, separated by a few hundred micrometre wide low dose regions. Abundant preclinical evidence demonstrates that MRT spares normal tissue more effectively than conventional radiation therapy, at equivalent tumour control. In order to launch first clinical trials, accurate and efficient dose calculation methods are an inevitable prerequisite. In this work a hybrid dose calculation approach is presented that is based on a combination of Monte Carlo and kernel based dose calculation. In various examples the performance of the algorithm is compared to purely Monte Carlo and purely kernel based dose calculations. The accuracy of the developed algorithm is comparable to conventional pure Monte Carlo calculations. In particular for inhomogeneous materials the hybrid dose calculation algorithm out-performs purely convolution based dose calculation approaches. It is demonstrated that the hybrid algorithm can efficiently calculate even complicated pencil beam and cross firing beam geometries. The required calculation times are substantially lower than for pure Monte Carlo calculations.

摘要

微束放射治疗(MRT)仍是放射肿瘤学中的一种临床前方法,它使用极高峰剂量的平面微米宽射束,通过几百微米宽的低剂量区域隔开。大量的临床前证据表明,MRT 在等效肿瘤控制的情况下,比传统放射治疗更有效地保护正常组织。为了开展首次临床试验,准确高效的剂量计算方法是一个必然的前提。在这项工作中,提出了一种混合剂量计算方法,它基于蒙特卡罗和基于核的剂量计算的组合。在各种示例中,将算法的性能与纯蒙特卡罗和纯基于核的剂量计算进行了比较。所开发算法的准确性可与传统的纯蒙特卡罗计算相媲美。特别是对于非均匀材料,混合剂量计算算法优于纯卷积剂量计算方法。已经证明,混合算法可以有效地计算甚至复杂的铅笔束和交叉照射束几何形状。所需的计算时间远低于纯蒙特卡罗计算。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6ef4/5964549/238699767e28/pmbaaa705f01_hr.jpg

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