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细胞周期时间与肿瘤控制概率。

Cell-cycle times and the tumour control probability.

作者信息

Maler Adrian, Lutscher Frithjof

机构信息

Department of Mathematics and Statistics, University of Ottawa, 585 King Edward Avenue, Ottawa, Ontario, Canada K1N 6N5.

出版信息

Math Med Biol. 2010 Dec;27(4):313-42. doi: 10.1093/imammb/dqp024. Epub 2009 Dec 6.

Abstract

Mechanistic dynamic cell population models for the tumour control probability (TCP) to date have used a simplistic representation of the cell cycle: either an exponential cell-cycle time distribution (Zaider & Minerbo, 2000, Tumour control probability: a formulation applicable to any temporal protocol of dose delivery. Phys. Med. Biol., 45, 279-293) or a two-compartment model (Dawson & Hillen, 2006, Derivation of the tumour control probability (TCP) from a cell cycle model. Comput. Math. Methods Med., 7, 121-142; Hillen, de Vries, Gong & Yurtseven, 2009, From cell population models to tumour control probability: including cell cycle effects. Acta Oncol. (submitted)). Neither of these simplifications captures realistic cell-cycle time distributions, which are rather narrowly peaked around the mean. We investigate how including such distributions affects predictions of the TCP. At first, we revisit the so-called 'active-quiescent' model that splits the cell cycle into two compartments and explore how an assumption of compartmental independence influences the predicted TCP. Then, we formulate a deterministic age-structured model and a corresponding branching process. We find that under realistic cell-cycle time distributions, lower treatment intensities are sufficient to obtain the same TCP as in the aforementioned models with simplified cell cycles, as long as the treatment is constant in time. For fractionated treatment, the situation reverses such that under realistic cell-cycle time distributions, the model requires more intense treatment to obtain the same TCP.

摘要

迄今为止,用于肿瘤控制概率(TCP)的机械动力学细胞群体模型采用了细胞周期的简单表示:要么是指数细胞周期时间分布(Zaider和Minerbo,2000年,《肿瘤控制概率:适用于任何剂量递送时间方案的公式》。《物理医学与生物学》,45卷,279 - 293页),要么是双室模型(Dawson和Hillen,2006年,《从细胞周期模型推导肿瘤控制概率(TCP)》。《计算数学方法在医学中的应用》,7卷,121 - 142页;Hillen、de Vries、Gong和Yurtseven,2009年,《从细胞群体模型到肿瘤控制概率:包括细胞周期效应》。《肿瘤学学报》(已提交))。这些简化都没有捕捉到现实的细胞周期时间分布,其在均值附近峰值相当狭窄。我们研究纳入此类分布如何影响TCP的预测。首先,我们重新审视将细胞周期分为两个室的所谓“活跃 - 静止”模型,并探讨室独立性假设如何影响预测的TCP。然后,我们制定一个确定性年龄结构模型和一个相应的分支过程。我们发现,在现实的细胞周期时间分布下,只要治疗在时间上是恒定的,较低的治疗强度就足以获得与上述具有简化细胞周期的模型相同的TCP。对于分割治疗,情况则相反,即在现实的细胞周期时间分布下,该模型需要更强烈的治疗才能获得相同的TCP。

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