Optimal number and sizes of the doses in fractionated radiotherapy according to the LQ model.

IF 0.8 4区 数学 Q4 BIOLOGY Mathematical Medicine and Biology-A Journal of the Ima Pub Date : 2019-03-14 DOI:10.1093/imammb/dqx020
C Bruni, F Conte, F Papa, C Sinisgalli
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引用次数: 6

Abstract

We address a non-linear programming problem to find the optimal scheme of dose fractionation in cancer radiotherapy. Using the LQ model to represent the response to radiation of tumour and normal tissues, we formulate a constrained non-linear optimization problem in terms of the variables number and sizes of the dose fractions. Quadratic constraints are imposed to guarantee that the damages to the early and late responding normal tissues do not exceed assigned tolerable levels. Linear constraints are set to limit the size of the daily doses. The optimal solutions are found in two steps: i) analytical determination of the optimal sizes of the fractional doses for a fixed, but arbitrary number of fractions n; ii) numerical simulation of a sequence of the previous optima for n increasing, and for specific tumour classes. We prove the existence of a finite upper bound for the optimal number of fractions. So, the optimum with respect to n is found by means of a finite number of comparisons amongst the optimal values of the objective function at the first step. In the numerical simulations, the radiosensitivity and repopulation parameters of the normal tissue are fixed, while we investigate the behaviour of the optimal solution for wide variations of the tumour parameters, relating our optima to real clinical protocols. We recognize that the optimality of hypo or equi-fractionated treatment schemes depends on the value of the tumour radiosensitivity ratio compared to the normal tissue radiosensitivity. Fast growing, radioresistant tumours may require particularly short optimal treatments.

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根据LQ模型确定分段放疗中最优剂量数和剂量大小。
针对肿瘤放射治疗中剂量分割的最佳方案,提出了一个非线性规划问题。使用LQ模型来表示肿瘤和正常组织对辐射的响应,我们根据剂量分数的变量数量和大小,制定了一个约束非线性优化问题。二次约束是为了保证对早期和晚期反应的正常组织的损害不超过指定的可容忍水平。设定了线性约束来限制每日剂量的大小。最优解分为两个步骤:i)对一个固定但任意数目的分数n,解析确定分数剂量的最优大小;Ii)对n递增和特定肿瘤类别的先前最优序列进行数值模拟。证明了分数最优个数的有限上界的存在性。所以,关于n的最优值是通过在第一步中对目标函数的最优值进行有限次比较来找到的。在数值模拟中,正常组织的放射敏感性和再生参数是固定的,而我们研究了肿瘤参数广泛变化的最佳解决方案的行为,将我们的最佳方案与实际临床方案联系起来。我们认识到,低分级或等分级治疗方案的最佳性取决于肿瘤放射敏感性比与正常组织放射敏感性的值。快速生长的耐辐射肿瘤可能需要特别短的最佳治疗。
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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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