PERSONALISED MODELLING OF VIRCHOW'S TRIAD FOR STROKE RISK ASSESSMENT IN ATRIAL FIBRILLATION

用于心房颤动中风​​风险评估的 Virchow 三联征的个性化建模

• 批准号: 2288490
• 金额: --
• 依托单位: King's College London
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2019
• 资助国家: 英国
• 起止时间: 2019 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2288490
• 关键词: PERSONALISED; MODELLING; VIRCHOW; TRIAD; STROKE

Atrial Fibrillation (AF) is the most prevalent cardiac arrhythmia in clinical settings and is brought about by a series of uncoordinated electrical activations which diminish the mechanical function of the left atrium (LA). Consequently, AF is reported to increase the risk of stroke five-fold which may be attributed to increased blood stasis, endothelial damage and hypercoagubility in the LA, all of which are physiological factors thought to promote thrombosis in Virchow's Triad. Currently, stroke risk stratification for AF patients is performed using the CHA2DS2-VASc scores and is based on empirical population information. Oral anticoagulants (OACs) or novel OACs are prescribed to patients with moderate-to-high risk of stroke. However, these risk scores provide little information to assess if low-risk patients, where OACs are not given, are truly low-risk, given that termination of AF by catheter ablation may result in impaired contractility and may promote blood stasis. This investigation aims to develop and use mechanistic computational fluid dynamic models to help determine the propensity of clot formation in patients who are classified as low risk using current risk stratification indices.To achieve this goal, I will develop a workflow for performing 3D blood flow simulations on patient-specific LA geometries. 3D models will be reconstructed from time-varying Cine MRI data with motion-tracking applied through MIRTK routines. All flow simulations will be performed using our in-house finite-element based biomechanics simulator, CHeart, with mathematical modelling of blood coagulation implemented through reaction-diffusion-convection equations. CHeart will be used to simulate small-scale biochemical reactions of blood coagulation alongside large-scale 3D fluid dynamics in the LA. This will allow for personalised predictions of the likelihood of thrombus formation which can supplement current risk scores. Findings to be validated using 4D Flow MRI.

心房颤动(房颤)是临床上最常见的心律失常，由一系列不协调的电刺激导致左心房(LA)机械功能减退所致。因此，据报道，房颤使中风的风险增加五倍，这可能归因于LA血瘀症、内皮损伤和高凝状态的增加，所有这些都被认为是促进Virchow三联症中血栓形成的生理因素。目前，房颤患者的卒中风险分层是使用CHA2DS2-VASc评分进行的，并基于经验人群信息。口服抗凝剂(OAC)或新型OAC被开给中到高中风风险的患者。然而，考虑到通过导管消融终止房颤可能导致收缩功能受损并可能促进血瘀证，这些风险评分提供的信息很少用于评估未给予OAC的低风险患者是否真的低风险。这项研究旨在开发和使用机械计算流体动力学模型来帮助确定使用当前风险分层指标被归类为低风险的患者的血栓形成倾向。为了实现这一目标，我将开发一个在患者特定的LA几何形状上执行3D血流模拟的工作流程。3D模型将从时变的电影MRI数据中重建，并通过MIRTK例程应用运动跟踪。所有的流动模拟都将使用我们内部基于有限元的生物力学模拟器CHART进行，其中血液凝固的数学模型通过反应-扩散-对流方程来实现。CHART将被用于模拟洛杉矶的血液凝固的小规模生化反应以及大规模的3D流体动力学。这将允许对血栓形成可能性的个性化预测，这可以补充当前的风险评分。检查结果将使用4D Flow MRI进行验证。