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Mass transfer modeling of solid tumor growth for therapy evaluation and prognosis

机译:实体肿瘤生长治疗评估和预后的传质建模

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Simulation of tumor evolution at the macroscopic, tissue scale can be applied to cancer treatment optimization. This paper aims to gain deeper insight into the dynamics of tumor growth at this scale and to develop predictive, quantitative mathematical models which can be used as a decision tool supporting oncologists and surgeons. This preliminary model describes tumor progression as mass transfer governed by partial differential equations, incorporating a multi-species logistic growth/decay law to account for the production of necrosis and the interaction with therapy. The set of governing equations is integrated by a commercial platform of Finite Element Method. After a validation study with literature data on a hepatocellular carcinoma, a sensitivity analysis was conducted by including the driving source terms (growth rates, drug efficiency and its delivery/availability). Results suggest that, in the first two months of therapy, tumor volume progress is related nonlinearly so that a mere 10% of stronger/weaker cancer malignancy lead to doubling/halving the tumor volume, the increment of drug efficiency by 25% lead to a 60% decrease of the volume, while a smaller efficiency by 25% lead to a sudden runaway of the disease. Finally, the optimal administration pattern for chemoembolization was found with a 4-points therapy delivery on the same side with respect to the Region of Interest.
机译:肿瘤演化在宏观上的仿真,组织规模可应用于癌症治疗优化。本文旨在深入了解肿瘤生长的动态,并开发可用作支持诱导员和外科医生的决策工具的预测性的定量数学模型。该初步模型描述了肿瘤进展作为偏微分方程所治理的传质,其中包含多种物流生长/腐烂法,以占坏死的产生和与治疗的相互作用。该组管理方程由有限元方法的商业平台集成。在对肝细胞癌的文献数据进行验证研究之后,通过包括驱动源术语(生长率,药物效率及其递送/可用性)进行敏感性分析。结果表明,在治疗的前两个月的治疗中,肿瘤体积进展是无线的,因此仅仅是10%的较强/越来越弱的癌症恶性肿瘤导致肿瘤的量加倍,药物效率的增量将递增25%升至a体积减少60%,而效率较小25%导致疾病的突然失控。最后,发现了用于化疗栓塞的最佳施用模式,在与感兴趣区域相同的同一方面的4点治疗递送。

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