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Mathematical modeling and analysis of tumor-volume variation during radiotherapy

机译:放射治疗过程中肿瘤体积变异的数学建模与分析

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摘要

Based on tumor radiobiologic mechanisms, this paper develops a new tumor growth dynamic model with radiotherapy. It investigates how the reoxygenation of hypoxic cells and the radiosensitivity of radiotherpy influence the effect of tumor radiotherapy. The existence of the positive periodic solution, the asymptotic stabilities of the tumor-free equilibrium and the hypoxic tumor cell-free periodic solution and the corresponding sufficient criteria are obtained in this paper. The theoretical results indicate that when the value of the sensitivity coefficient of radiotherapy becomes bigger and the reoxygenation rate of tumor cells becomes higher, the radiotherapy of tumor is more effective. In addition, we apply our model to simulate the volumetric imaging data from 12 available head-and-neck cancer patients treated with an integrated computed tomography/linear accelerator system and obtain a very good fitting effect. Finally, we apply patient specific parameters obtained by simulating clinical data of 12 tumor cases to investigate their individual similarities and differences, so that we can provide some guidance for medical workers to implement personalized treatment strategies for tumor patients.
机译:基于肿瘤辐射生物机制,本文开发了一种新的肿瘤生长动态模型,具有放射疗法。它研究了缺氧细胞的雷诺雷氧化和放射疗法的放射敏感性如何影响肿瘤放射疗法的作用。阳性周期性溶液的存在性,无肿瘤平衡和缺氧肿瘤无细胞周期性溶液和相应的足够标准的渐近稳定性。理论结果表明,当放射疗法敏感系数的值变得更大并且肿瘤细胞的雷氧化率变得更高时,肿瘤的放射疗法更有效。此外,我们应用我们的模型来模拟来自12种可用的头颈癌症患者的体积成像数据,该癌症患者用集成的计算机断层扫描/线性加速器系统获得并获得了非常好的拟合效果。最后,我们通过模拟12肿瘤病例的临床数据来研究患者的特定参数来调查其个体相似之处和差异,以便我们为医疗工作者提供一些指导,以便为肿瘤患者实施个性化治疗策略。

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