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Computational fluid dynamic simulations informed by CT and 4D flow MRI for post-surgery aortic dissection – A case study

主动脉夹层 升主动脉 主动脉 医学 血流动力学 降主动脉 放射科 磁共振成像 胸主动脉 管腔(解剖学) 心脏病学 内科学
作者
Qingdi Wang,Xiaojing Guo,Daniel Stäb,Ning Jin,Eric Poon,Ruth P. Lim,Andrew Ooi
出处
期刊:International Journal of Heat and Fluid Flow [Elsevier]
卷期号:96: 108986-108986 被引量:10
标识
DOI:10.1016/j.ijheatfluidflow.2022.108986
摘要

Aortic dissection is a serious pathological condition where tears in the aortic wall allow blood to flow between layers of the aortic wall, separating tissue and creating a false lumen, with type A dissection affecting the ascending aorta. The considerable change in post-surgical type A dissection morphology, with residual dissection within the descending aorta, significantly alters blood flow dynamics. Knowledge of haemodynamics in this patient population may provide greater insight into disease progression. Patient-specific computational fluid dynamics (CFD) can provide this haemodynamic information to assist clinicians in assessing timing and appropriateness of intervention to prevent long-term complications. In this work, an approach integrating anatomic data from CT and personalised haemodynamics derived from 4D flow magnetic resonance imaging (4D flow MRI) with CFD in qualitative and quantitative analyses of intra-aortic flow is presented for a patient with residual aortic dissection after ascending aortic repair for type A dissection. Results show good agreement between simulated flow and 4D flow MRI measurements in the aorta, but with discrepancies observed in the false lumen. Multiple recirculation zones are observed in the thoracic false lumen, which is likely to beassociated with thrombus deposition. Regions of lower time-averaged wall shear stress (WSS) and high pressure differences between true and false lumens were found, identified as risk factors for false lumen dilation in the literature. Regions of high time-averaged WSS are detected in the aorta adjacent to entrances and exits of the false lumen. WSS is regarded as a critical biomechanical factor in disease progression, and detailed analysis of computer derived WSS could in future provide evidence-based recommendations for clinical management.

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