Biomechanical stress analysis of Type-A aortic dissection at pre-dissection, post-dissection, and post-repair states

被引:0
|
作者
Sun, Christina [1 ]
Qin, Tongran [1 ]
Kalyanasundaram, Asanish [2 ]
Elefteriades, John [2 ]
Sun, Wei [1 ]
Liang, Liang [3 ]
机构
[1] Sutra Medical Inc, Lake Forest,CA, United States
[2] Aortic Institute at Yale-New Haven Hospital, Yale University School of Medicine, New Haven,CT, United States
[3] Department of Computer Science, University of Miami, Coral Gables,FL, United States
基金
美国国家卫生研究院;
关键词
Dissection - Residual stresses - Risk analysis - Risk perception - Stress analysis - Stress concentration - Surgery;
D O I
10.1016/j.compbiomed.2024.109310
中图分类号
学科分类号
摘要
Acute type A aortic dissection remains a deadly and elusive condition, with risk factors such as hypertension, bicuspid aortic valves, and genetic predispositions. As existing guidelines for surgical intervention based solely on aneurysm diameter face scrutiny, there is a growing need to consider other predictors and parameters, including wall stress, in assessing dissection risk. Through our research, we aim to elucidate the biomechanical underpinnings of aortic dissection and provide valuable insights into its prediction and prevention. We applied finite element analysis (FEA) to assess stress distribution on a rare dataset comprising computed tomography (CT) images obtained from eight patients at three stages of aortic dissection: pre-dissection (preD), post-dissection (postD), and post-repair (postR). Our findings reveal significant increases in both mean and peak aortic wall stresses during the transition from the preD state to the postD state, reflecting the mechanical impact of dissection. Surgical repair effectively restores aortic wall diameter to pre-dissection levels, documenting its effectiveness in mitigating further complications. Furthermore, we identified stress concentration regions within the aortic wall that closely correlated with observed dissection borders, offering insights into high-risk areas. This study demonstrates the importance of considering biomechanical factors when assessing aortic dissection risk. Despite some limitations, such as uniform wall thickness assumptions and the absence of dynamic blood flow considerations, our patient-specific FEA approach provides valuable mechanistic insights into aortic dissection. These findings hold promise for improving predictive models and informing clinical decisions to enhance patient care. © 2024 Elsevier Ltd
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