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时机问题:通过数值模拟和遗传算法搜索确定多剂量放射治疗的显著改进

A matter of timing: identifying significant multi-dose radiotherapy improvements by numerical simulation and genetic algorithm search.

作者信息

Angus Simon D, Piotrowska Monika Joanna

机构信息

Department of Economics, Monash University, Melbourne, Victoria, Australia.

Faculty of Mathematics Informatics and Mechanics, Institute of Applied Mathematics and Mechanics, University of Warsaw, Warsaw, Mazowieckie, Poland.

出版信息

PLoS One. 2014 Dec 2;9(12):e114098. doi: 10.1371/journal.pone.0114098. eCollection 2014.

Abstract

Multi-dose radiotherapy protocols (fraction dose and timing) currently used in the clinic are the product of human selection based on habit, received wisdom, physician experience and intra-day patient timetabling. However, due to combinatorial considerations, the potential treatment protocol space for a given total dose or treatment length is enormous, even for relatively coarse search; well beyond the capacity of traditional in-vitro methods. In constrast, high fidelity numerical simulation of tumor development is well suited to the challenge. Building on our previous single-dose numerical simulation model of EMT6/Ro spheroids, a multi-dose irradiation response module is added and calibrated to the effective dose arising from 18 independent multi-dose treatment programs available in the experimental literature. With the developed model a constrained, non-linear, search for better performing cadidate protocols is conducted within the vicinity of two benchmarks by genetic algorithm (GA) techniques. After evaluating less than 0.01% of the potential benchmark protocol space, candidate protocols were identified by the GA which conferred an average of 9.4% (max benefit 16.5%) and 7.1% (13.3%) improvement (reduction) on tumour cell count compared to the two benchmarks, respectively. Noticing that a convergent phenomenon of the top performing protocols was their temporal synchronicity, a further series of numerical experiments was conducted with periodic time-gap protocols (10 h to 23 h), leading to the discovery that the performance of the GA search candidates could be replicated by 17-18 h periodic candidates. Further dynamic irradiation-response cell-phase analysis revealed that such periodicity cohered with latent EMT6/Ro cell-phase temporal patterning. Taken together, this study provides powerful evidence towards the hypothesis that even simple inter-fraction timing variations for a given fractional dose program may present a facile, and highly cost-effecitive means of significantly improving clinical efficacy.

摘要

目前临床上使用的多剂量放射治疗方案(分次剂量和时间安排)是基于习惯、传统认知、医生经验以及日内患者时间安排进行人为选择的产物。然而,由于组合因素的考量,对于给定的总剂量或治疗时长,潜在的治疗方案空间极为庞大,即便进行相对粗略的搜索亦是如此;这远远超出了传统体外方法的能力范围。相比之下,肿瘤发展的高保真数值模拟非常适合应对这一挑战。基于我们之前关于EMT6/Ro球体的单剂量数值模拟模型,添加了一个多剂量照射反应模块,并根据实验文献中18个独立的多剂量治疗方案所产生的有效剂量进行校准。利用所开发的模型,通过遗传算法(GA)技术在两个基准附近进行了受限的非线性搜索,以寻找性能更优的候选方案。在评估了不到0.01%的潜在基准方案空间后,遗传算法确定了候选方案,与两个基准相比,这些方案分别使肿瘤细胞数量平均减少了9.4%(最大获益为16.5%)和7.1%(13.3%)。注意到表现最佳的方案的一个趋同现象是它们的时间同步性,于是对周期性时间间隔方案(10小时至23小时)进行了一系列进一步的数值实验,结果发现遗传算法搜索候选方案的性能可以被17 - 18小时的周期性候选方案复制。进一步的动态照射反应细胞阶段分析表明,这种周期性与潜在的EMT6/Ro细胞阶段时间模式相一致。综上所述,本研究为以下假设提供了有力证据:即使对于给定的分次剂量方案,简单的分次间时间变化也可能是一种简便且极具成本效益的显著提高临床疗效的方法。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d1fc/4252029/cfb5b89f1e12/pone.0114098.g001.jpg

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