脑动脉瘤进展的生物力学模型估计破裂风险

Prem Nath Yadav, Gurpreet Singh, Shubham Gupta, A. Chanda
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引用次数: 1

摘要

脑动脉瘤是一种医学状况,被描述为在不利压力条件下大脑动脉膨出。患有这种疾病的患者由于动脉瘤破裂导致的死亡率为20%,额外发病率为30-40%。目前使用的成像工具,如MRI和CT扫描,只提供动脉瘤的几何信息,而不提供与动脉瘤进展相关的破裂风险。开发了一种新的计算建模框架来模拟动脉瘤的进展,并评估在不同压力载荷条件下的应力分布,以弥补这一差距。图像分割用于分割两条大脑中动脉(MCA),并重建以设计脆弱部位的动脉瘤模型,用于模拟动脉瘤进展。对五种大小和两种不同壁厚的动脉瘤进行建模,以模拟动脉瘤进展的不同阶段。采用三种压力(即舒张压、收缩压和高血压)来模拟大脑中动脉的真实压力负荷情景,并估计所有模型的应力分布,以了解破裂风险。观察到动脉瘤壁中的诱导应力随着动脉瘤直径和血压的增加而增加。此外,直径大、壁薄的动脉瘤破裂的风险很高,尤其是在高血压情况下。预计报告的结果将帮助医生预测已知的基于成像的动脉瘤大小的破裂风险,并及时对此类动脉瘤情况做出决定。
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Biomechanical Modeling of Cerebral Aneurysm Progression to Estimate Rupture Risk
A cerebral aneurysm is a medical condition described as the bulging out of the cerebral artery under adverse pressure conditions. Patients with such medical conditions have a mortality of 20% and additional morbidity of 30–40% due to aneurysm rupture. The currently used imaging tools such as MRI and CT scans only provide geometrical information of the aneurysm and not the rupture risk associated with the progression of the aneurysm. A novel computational modeling framework was developed to model aneurysm progression and evaluate the stress distribution under varying pressure loading conditions to bridge this gap. Image segmentation was used to segment two middle cerebral arteries (MCA) and reconstructed to design aneurysm models at vulnerable sites for aneurysm progression simulation. Five aneurysm sizes and two different wall thicknesses were modeled to simulate different stages of aneurysm progression. Three pressures (i.e., diastolic, systolic, and hypertensive) were adopted to mimic the realistic pressure loading scenario for the middle cerebral arteries, and the stress distributions across all the models were estimated to understand the rupture risk. It was observed that the induced stresses in the aneurysm walls increased with an increase in the aneurysm diameter and blood pressure. Additionally, an aneurysm with a large diameter and thin walls exhibited a high risk of rupture, especially at high blood pressures. The reported results are anticipated to help medical practitioners predict rupture risks with known imaging-based aneurysm sizes and make timely decisions for such aneurysm conditions.
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