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颅内动脉瘤的虚拟血管内治疗:模型与不确定性

Virtual endovascular treatment of intracranial aneurysms: models and uncertainty.

作者信息

Sarrami-Foroushani Ali, Lassila Toni, Frangi Alejandro F

机构信息

Center for Computational Imaging and Simulation Technologies in Biomedicine (CISTIB), The University of Sheffield, Sheffield, UK.

出版信息

Wiley Interdiscip Rev Syst Biol Med. 2017 Jul;9(4). doi: 10.1002/wsbm.1385. Epub 2017 May 10.

Abstract

Virtual endovascular treatment models (VETMs) have been developed with the view to aid interventional neuroradiologists and neurosurgeons to pre-operatively analyze the comparative efficacy and safety of endovascular treatments for intracranial aneurysms. Based on the current state of VETMs in aneurysm rupture risk stratification and in patient-specific prediction of treatment outcomes, we argue there is a need to go beyond personalized biomechanical flow modeling assuming deterministic parameters and error-free measurements. The mechanobiological effects associated with blood clot formation are important factors in therapeutic decision making and models of post-treatment intra-aneurysmal biology and biochemistry should be linked to the purely hemodynamic models to improve the predictive power of current VETMs. The influence of model and parameter uncertainties associated to each component of a VETM is, where feasible, quantified via a random-effects meta-analysis of the literature. This allows estimating the pooled effect size of these uncertainties on aneurysmal wall shear stress. From such meta-analyses, two main sources of uncertainty emerge where research efforts have so far been limited: (1) vascular wall distensibility, and (2) intra/intersubject systemic flow variations. In the future, we suggest that current deterministic computational simulations need to be extended with strategies for uncertainty mitigation, uncertainty exploration, and sensitivity reduction techniques. WIREs Syst Biol Med 2017, 9:e1385. doi: 10.1002/wsbm.1385 For further resources related to this article, please visit the WIREs website.

摘要

虚拟血管内治疗模型(VETMs)的开发旨在帮助介入神经放射科医生和神经外科医生在术前分析颅内动脉瘤血管内治疗的相对疗效和安全性。基于VETMs在动脉瘤破裂风险分层和患者特异性治疗结果预测方面的现状,我们认为有必要超越假设参数确定且测量无误差的个性化生物力学血流建模。与血栓形成相关的机械生物学效应是治疗决策的重要因素,治疗后动脉瘤内生物学和生物化学模型应与纯血流动力学模型相联系,以提高当前VETMs的预测能力。在可行的情况下,通过对文献的随机效应荟萃分析来量化与VETM每个组成部分相关的模型和参数不确定性的影响。这有助于估计这些不确定性对动脉瘤壁剪应力的合并效应大小。从这样的荟萃分析中,出现了两个目前研究工作有限的主要不确定性来源:(1)血管壁扩张性,以及(2)个体内/个体间全身血流变化。未来,我们建议当前的确定性计算模拟需要扩展不确定性缓解、不确定性探索和敏感性降低技术等策略。WIREs系统生物学与医学2017年,9:e1385。doi:10.1002/wsbm.1385 有关本文的更多资源,请访问WIREs网站。

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