体外放射治疗的最佳模式选择。

IF 0.8 4区 数学 Q4 BIOLOGY
Sevnaz Nourollahi, Archis Ghate, Minsun Kim
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引用次数: 4

摘要

治疗癌症的外部放射治疗(EBRT)的目标是最大限度地损害肿瘤,同时限制对危险器官的毒性作用。EBRT可以通过光子、质子和中子等不同的方式输送。最佳模态的选择取决于被照射区域的解剖结构以及所考虑的模态的相对物理和生物特性。没有单一的、普遍占主导地位的模态。我们提出了第一个最优模态选择问题的数学公式。我们证明这个问题可以通过求解最优性的Karush-Kuhn-Tucker条件来解决,该条件可以简化为可解析处理的四次方程。我们进行数值实验,以深入了解生物和物理特性对选择最佳模态或模态组合的影响。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Optimal modality selection in external beam radiotherapy.

The goal in external beam radiotherapy (EBRT) for cancer is to maximize damage to the tumour while limiting toxic effects on the organs-at-risk. EBRT can be delivered via different modalities such as photons, protons and neutrons. The choice of an optimal modality depends on the anatomy of the irradiated area and the relative physical and biological properties of the modalities under consideration. There is no single universally dominant modality. We present the first-ever mathematical formulation of the optimal modality selection problem. We show that this problem can be tackled by solving the Karush-Kuhn-Tucker conditions of optimality, which reduce to an analytically tractable quartic equation. We perform numerical experiments to gain insights into the effect of biological and physical properties on the choice of an optimal modality or combination of modalities.

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来源期刊
CiteScore
2.20
自引率
0.00%
发文量
15
审稿时长
>12 weeks
期刊介绍: Formerly the IMA Journal of Mathematics Applied in Medicine and Biology. Mathematical Medicine and Biology publishes original articles with a significant mathematical content addressing topics in medicine and biology. Papers exploiting modern developments in applied mathematics are particularly welcome. The biomedical relevance of mathematical models should be demonstrated clearly and validation by comparison against experiment is strongly encouraged. The journal welcomes contributions relevant to any area of the life sciences including: -biomechanics- biophysics- cell biology- developmental biology- ecology and the environment- epidemiology- immunology- infectious diseases- neuroscience- pharmacology- physiology- population biology
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