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
收藏
页码：23 / 34
页数：12
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