在缺血性中风中,再灌注治疗后,血液供应的大量减少会导致血脑屏障的破坏和脑水肿。脑水肿的特征是颅内压(ICP)升高,组织疝和脑灌注压降低。在临床环境中,渗透疗法一直是降低ICP的常见做法。然而,没有关于选择给药方案参数的指南,例如注射剂量,输注时间和保留时间。最重要的是,渗透疗法的效果已被证明是有争议的,因为渗透剂的输注会导致一系列的副作用。这里,因此,提出了一种新的脑水肿和渗透治疗的有限元模型来预测治疗结果。该模型由模拟血液灌注的三个组件组成,水肿,和渗透疗法,分别。在灌注模型(包括小动脉,静脉,和毛细血管血液隔室),解剖学上准确的大脑几何形状用于识别在中风中灌注减少和潜在水肿发生的区域。然后使用具有四个流体隔室的多孔循环模型(小动脉血液,静脉血,毛细血管血,和间质液)。在渗透疗法模型中,渗透压是变化的,并且在不同渗透治疗期间ICP的变化被量化。该模型的模拟结果与可用的临床数据显示出极好的一致性,并且该模型用于研究各种参数下的渗透治疗。因此,通过模拟,证明了如何为具有不同病理参数的患者提出治疗策略.
In ischaemic stroke, a large reduction in blood supply can lead to the breakdown of the blood brain barrier and to cerebral oedema after reperfusion therapy. Cerebral oedema is marked by elevated intracranial pressure (ICP), tissue herniation and reduced cerebral perfusion pressure. In clinical settings, osmotherapy has been a common practice to decrease ICP. However, there are no guidelines on the choice of administration protocol parameters such as injection doses, infusion time and retention time. Most importantly, the effects of osmotherapy have been proven controversial since the infusion of osmotic agents can lead to a range of side effects. Here, a new Finite Element model of brain oedema and osmotherapy is thus proposed to predict treatment outcome. The model consists of three components that simulate blood perfusion, oedema, and osmotherapy, respectively. In the perfusion model (comprising arteriolar, venous, and capillary blood compartments), an anatomically accurate brain geometry is used to identify regions with a perfusion reduction and potential oedema occurrence in stroke. The oedema model is then used to predict ICP using a porous circulation model with four fluid compartments (arteriolar blood, venular blood, capillary blood, and interstitial fluid). In the osmotherapy model, the osmotic pressure is varied and the changes in ICP during different osmotherapy episodes are quantified. The simulation results of the model show excellent agreement with available clinical data and the model is employed to study osmotherapy under various parameters. Consequently, it is demonstrated how therapeutic strategies can be proposed for patients with different pathological parameters based on simulations.