Ngoepe Malebogo N, Frangi Alejandro F, Byrne James V, Ventikos Yiannis
Department of Mechanical Engineering, University of Cape Town, Cape Town, South Africa.
Centre for High Performance Computing, Council for Scientific and Industrial Research, Cape Town, South Africa.
Front Physiol. 2018 Apr 4;9:306. doi: 10.3389/fphys.2018.00306. eCollection 2018.
Thrombosis is a condition closely related to cerebral aneurysms and controlled thrombosis is the main purpose of endovascular embolization treatment. The mechanisms governing thrombus initiation and evolution in cerebral aneurysms have not been fully elucidated and this presents challenges for interventional planning. Significant effort has been directed towards developing computational methods aimed at streamlining the interventional planning process for unruptured cerebral aneurysm treatment. Included in these methods are computational models of thrombus development following endovascular device placement. The main challenge with developing computational models for thrombosis in disease cases is that there exists a wide body of literature that addresses various aspects of the clotting process, but it may not be obvious what information is of direct consequence for what modeling purpose (e.g., for understanding the effect of endovascular therapies). The aim of this review is to present the information so it will be of benefit to the community attempting to model cerebral aneurysm thrombosis for interventional planning purposes, in a simplified yet appropriate manner. The paper begins by explaining current understanding of physiological coagulation and highlights the documented distinctions between the physiological process and cerebral aneurysm thrombosis. Clinical observations of thrombosis following endovascular device placement are then presented. This is followed by a section detailing the demands placed on computational models developed for interventional planning. Finally, existing computational models of thrombosis are presented. This last section begins with description and discussion of physiological computational clotting models, as they are of immense value in understanding how to construct a general computational model of clotting. This is then followed by a review of computational models of clotting in cerebral aneurysms, specifically. Even though some progress has been made towards computational predictions of thrombosis following device placement in cerebral aneurysms, many gaps still remain. Answering the key questions will require the combined efforts of the clinical, experimental and computational communities.
血栓形成是一种与脑动脉瘤密切相关的病症,控制血栓形成是血管内栓塞治疗的主要目的。脑动脉瘤中血栓形成和演变的机制尚未完全阐明,这给介入治疗规划带来了挑战。人们已投入大量精力来开发计算方法,旨在简化未破裂脑动脉瘤治疗的介入治疗规划过程。这些方法包括血管内装置置入后血栓形成的计算模型。在针对疾病案例开发血栓形成计算模型时,主要挑战在于存在大量涉及凝血过程各个方面的文献,但对于何种建模目的(例如,用于理解血管内治疗的效果)哪些信息具有直接影响可能并不明显。本综述的目的是以简化但恰当的方式呈现这些信息,使其对试图为介入治疗规划对脑动脉瘤血栓形成进行建模的群体有益。本文首先解释了当前对生理凝血的理解,并强调了生理过程与脑动脉瘤血栓形成之间已记录的差异。接着介绍了血管内装置置入后血栓形成的临床观察结果。随后有一节详细说明了为介入治疗规划开发的计算模型所面临的要求。最后呈现了现有的血栓形成计算模型。最后这一部分首先描述和讨论生理计算凝血模型,因为它们在理解如何构建一般的凝血计算模型方面具有巨大价值。然后专门回顾了脑动脉瘤中的凝血计算模型。尽管在对脑动脉瘤中装置置入后血栓形成的计算预测方面已取得一些进展,但仍存在许多空白。回答关键问题需要临床、实验和计算领域的共同努力。