Mathematical modeling of radiotherapy: impact of model selection on estimating minimum radiation dose for tumor control.
Mathematical modeling of radiotherapy: impact of model selection on estimating minimum radiation dose for tumor control.
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DOI：
10.3389/fonc.2023.1130966
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发表时间：
2023
影响因子：
4.7
通讯作者：
中科院分区：
文献类型：
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放射治疗（RT）是最常见的抗癌疗法之一。然而，目前的放射肿瘤学实践并不适应RT剂量为个别患者，尽管广泛的患者间的放射敏感性和伴随的治疗反应的变化。我们先前已经表明，肿瘤体积动力学的机械数学建模可以模拟个体患者对RT的体积反应，并估计个性化RT剂量以实现最佳肿瘤体积缩小。然而，理解的基础RT反应模型的选择的影响是至关重要的，当计算个性化的RT剂量。在这项研究中，我们评估了2种RT反应模型对剂量个性化的数学含义和生物学效应：（1）对癌细胞的细胞毒性，导致直接肿瘤体积缩小（DVR）和（2）对肿瘤微环境的辐射反应，导致肿瘤携带能力降低（CCR）和随后的肿瘤缩小。肿瘤生长模拟为逻辑生长，处理前动力学以增殖饱和指数（PSI）描述。根据每个相应的模型模拟RT的效果，采用2戈伊工作日分次的标准分次RT时间表。对两种模型的内在肿瘤生长速率和放射敏感性参数进行参数扫描，以观察每个模型参数的定性影响。然后，我们计算了局部肿瘤控制（LRC）所需的最小RT剂量，所有组合的全范围的放射敏感性和增殖饱和值。 两种模型都估计，放射敏感性较高的患者需要较低的RT剂量才能达到LRC。然而，这两个模型对PSI对LRC最小RT剂量的影响做出了相反的估计：DVR模型估计PSI值较高的肿瘤将需要较高的RT剂量才能实现LRC，而CCR模型估计PSI值较高的肿瘤将需要较低的RT剂量才能实现LRC。最终，这些结果表明，在使用任何此类模型对个性化治疗建议进行估计之前，了解哪种模型最能描述特定环境中的肿瘤生长和治疗反应非常重要。
Radiation therapy (RT) is one of the most common anticancer therapies. Yet, current radiation oncology practice does not adapt RT dose for individual patients, despite wide interpatient variability in radiosensitivity and accompanying treatment response. We have previously shown that mechanistic mathematical modeling of tumor volume dynamics can simulate volumetric response to RT for individual patients and estimation personalized RT dose for optimal tumor volume reduction. However, understanding the implications of the choice of the underlying RT response model is critical when calculating personalized RT dose. In this study, we evaluate the mathematical implications and biological effects of 2 models of RT response on dose personalization: (1) cytotoxicity to cancer cells that lead to direct tumor volume reduction (DVR) and (2) radiation responses to the tumor microenvironment that lead to tumor carrying capacity reduction (CCR) and subsequent tumor shrinkage. Tumor growth was simulated as logistic growth with pre-treatment dynamics being described in the proliferation saturation index (PSI). The effect of RT was simulated according to each respective model for a standard schedule of fractionated RT with 2 Gy weekday fractions. Parameter sweeps were evaluated for the intrinsic tumor growth rate and the radiosensitivity parameter for both models to observe the qualitative impact of each model parameter. We then calculated the minimum RT dose required for locoregional tumor control (LRC) across all combinations of the full range of radiosensitvity and proliferation saturation values. Both models estimate that patients with higher radiosensitivity will require a lower RT dose to achieve LRC. However, the two models make opposite estimates on the impact of PSI on the minimum RT dose for LRC: the DVR model estimates that tumors with higher PSI values will require a higher RT dose to achieve LRC, while the CCR model estimates that higher PSI values will require a lower RT dose to achieve LRC. Ultimately, these results show the importance of understanding which model best describes tumor growth and treatment response in a particular setting, before using any such model to make estimates for personalized treatment recommendations.
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影响因子：
6.2
作者：
Delaney, G;Jacob, S;Barton, M
通讯作者：
Barton, M
影响因子：
3.8
作者：
Dahlman, Erik L.;Watanabe, Yoichi
通讯作者：
Watanabe, Yoichi
DOI：
10.1016/0360-3016(94)00419-l
发表时间：
1995-03-30
影响因子：
7
作者：
COIA, LR;MYERSON, RJ;TEPPER, JE
通讯作者：
TEPPER, JE
影响因子：
11.5
作者：
Eschrich, Steven A.;Fulp, William J.;Torres-Roca, Javier F.
通讯作者：
Torres-Roca, Javier F.
影响因子：
3.4
作者：
Brú, A;Albertos, S;Brú, I
通讯作者：
Brú, I