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Malignant Glioma Progression and Response to Therapy In Silico

机译:恶性胶质瘤进展和对计算机的治疗反应

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We present a multi-scale computer simulator of cancer progression at the tumoral level, from avascular stage growth, through the transition from avascular to vascular growth (neo-vascularization), and into the later stages of growth and invasion of normal tissue. We use continuum scale reaction-diffusion equations for the growth component of the model, and a combined continuum-discrete model for the angiogenesis component. We use the level set method for describing complex topological changes observed during growth such as tumor splitting and reconnection, and capture of healthy tissue inside the tumor. We use an adaptive, unstructured finite element mesh that allows for finely resolving important regions of the computational domain such as the necrotic rim, the tumor interface and around the capillary sprouts. We present full nonlinear, two-dimensional simulations, showing the potential of our virtual cancer simulator. We use microphysical parameters characterizing malignant glioma cells, obtained from recent in vitro experiments from our lab and from clinical data, and provide insight into the mechanisms leading to infiltration of the brain by the cancer cells. The results indicate that diffusional instability of tumor mass growth and the complex interplay with the developing neo-vasculature may be powerful mechanisms for tissue invasion.
机译:我们提出了一个多尺度的计算机模拟器,用于从肿瘤的无血管阶段生长到无血管到血管生长(新血管形成)过渡到正常组织的晚期生长和浸润的肿瘤发展过程。我们对模型的增长成分使用连续尺度反应扩散方程,对血管生成成分使用组合的连续离散模型。我们使用水平集方法来描述在生长过程中观察到的复杂拓扑变化,例如肿瘤分裂和重新连接以及在肿瘤内部捕获健康组织。我们使用了自适应的,非结构化的有限元网格,可以很好地解决计算域的重要区域,例如坏死边缘,肿瘤界面以及毛细血管周围。我们提供了完整的非线性二维仿真,显示了我们虚拟癌症仿真器的潜力。我们使用表征实验室和临床数据的近期体外实验获得的恶性神经胶质瘤细胞的微物理参数,并深入了解导致癌细胞浸润大脑的机制。结果表明,肿瘤块生长的扩散不稳定性以及与正在发育的新脉管系统的复杂相互作用可能是组织入侵的强大机制。

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