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[低级别胶质瘤的数学建模]

[Mathematical modeling of low-grade glioma].

作者信息

Mandonnet Emmanuel

机构信息

Neurochirurgie, Hôpital de Lariboisière, 2 rue Ambroise Paré--75010 Paris.

出版信息

Bull Acad Natl Med. 2011 Jan;195(1):23-34; discussion 34-6.

Abstract

Magnetic resonance imaging can be used to quantify low-grade glioma growth with millimetric accuracy. Mathematical modeling helps to analyze individual glioma growth curves and tumor dynamics. Here we focus on the most extensively studied model, based on a proliferation-diffusion equation. We examine how this model offers a new quantitative approach to the natural history of low-grade glioma, including tumor kinetics and other well-known prognostic factors. This approach, based on quantitative imaging coupled with mathematical modeling, has the potential to help optimize treatment strategies.

摘要

磁共振成像可用于以毫米级精度量化低级别胶质瘤的生长情况。数学建模有助于分析个体胶质瘤的生长曲线和肿瘤动态。在此,我们聚焦于基于增殖 - 扩散方程的研究最为广泛的模型。我们研究该模型如何为低级别胶质瘤的自然史提供一种新的定量方法,包括肿瘤动力学及其他众所周知的预后因素。这种基于定量成像与数学建模相结合的方法,有潜力帮助优化治疗策略。

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