Mathematical modeling of low-grade glioma

被引：2

作者：

Mandonnet, Emmanuel ^{[1
]}

机构：

[1] Hop Lariboisiere, F-75010 Paris, France

来源：

BULLETIN DE L ACADEMIE NATIONALE DE MEDECINE | 2011年 / 195卷 / 01期

关键词：

GLIOMA; DIAGNOSTIC IMAGING; MAGNETIC RESONANCE IMAGING; MODELS; THEORETICAL; II GLIOMAS; GROWTH-RATES; SURGICAL RESECTION; BRAIN-TUMORS; TEMOZOLOMIDE; CHEMOTHERAPY; SURVIVAL; EXTENT; MANAGEMENT; HISTORY;

D O I：

10.1016/S0001-4079(19)32126-0

中图分类号：

R5 [内科学];

学科分类号：

1002 ; 100201 ;

摘要：

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.

引用

页码：23 / 34

页数：12

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