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热栓塞治疗的质量和能量传输的数学建模。

Mathematical modeling of mass and energy transport for thermoembolization.

机构信息

Department of Imaging Physics, Anderson Cancer Center, The University of Texas MD, Houston, TX, USA.

Department of Computational and Applied Mathematics, Rice University, Houston, TX, USA.

出版信息

Int J Hyperthermia. 2020;37(1):356-365. doi: 10.1080/02656736.2020.1749317.

Abstract

Thermoembolization presents a unique treatment alternative for patients diagnosed with hepatocellular carcinoma. The approach delivers a reagent that undergoes an exothermic chemical reaction and combines the benefits of embolic as well as thermal- and chemical-ablative therapy modalities. The target tissue and vascular bed are subjected to simultaneous hyperthermia, ischemia, and chemical denaturation in a single procedure. To guide optimal delivery, we developed a mathematical model for understanding the competing diffusive and convective effects observed in thermoembolization delivery protocols. A mixture theory formulation was used to mathematically model thermoembolization as chemically reacting transport of an electrophile, dichloroacetyl chloride (DCACl), within porous living tissue. Mass and energy transport of each relevant constituent are considered. Specifically, DCACl is injected into the vessels and exothermically reacts with water in the blood or tissue to form dichloroacetic acid and hydrochloric acid. Neutralization reactions are assumed instantaneous in this approach. We validated the mathematical model predictions of temperature using MR thermometry of the thermoembolization procedure performed in kidney. Mathematical modeling predictions of tissue death were highly dependent on the vascular geometry, injection pressure, and intrinsic amount of exothermic energy released from the chemical species, and were able to recapitulate the temperature distributions observed in MR thermometry. These efforts present a first step toward formalizing a mathematical model for thermoembolization and are promising for providing insight for delivery protocol optimization. While our approach captured the observed experimental temperature measurements, larger-scale experimental validation is needed to prioritize additional model complexity and fidelity.

摘要

热栓塞为诊断为肝细胞癌的患者提供了一种独特的治疗选择。该方法提供了一种试剂,该试剂经历放热化学反应,并结合了栓塞以及热和化学消融治疗方式的优点。在单个过程中,靶组织和血管床同时受到高热、缺血和化学变性的影响。为了指导最佳输送,我们开发了一种数学模型,以了解在热栓塞输送方案中观察到的扩散和对流竞争效应。使用混合物理论公式来对热栓塞进行数学建模,即将亲电试剂二氯乙酰氯(DCACl)作为化学反应在多孔活组织内进行传输。考虑了每个相关成分的质量和能量传输。具体来说,将 DCACl 注入血管中,并与血液或组织中的水发生放热反应,形成二氯乙酸和盐酸。在这种方法中,中和反应被假定为瞬时的。我们使用在肾脏中进行的热栓塞过程的磁共振测温来验证数学模型对温度的预测。组织死亡的数学模型预测高度依赖于血管几何形状、注射压力以及化学物质释放的内在放热能量,并且能够再现磁共振测温中观察到的温度分布。这些努力代表了为热栓塞形式化数学模型迈出的第一步,并有望为输送方案优化提供见解。虽然我们的方法捕获了观察到的实验温度测量值,但需要进行更大规模的实验验证,以确定模型的额外复杂性和保真度。

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