PolitoBIOMed Lab, Department of Mechanical and Aerospace Engineering, Politecnico di Torino, Turin, Italy.
Vall d'Hebron Institut de Recerca, Barcelona, Spain; Biomedical Research Networking Center on Cardiovascular Diseases, Instituto de Salud Carlos III, Madrid, Spain.
Comput Methods Programs Biomed. 2024 Oct;255:108369. doi: 10.1016/j.cmpb.2024.108369. Epub 2024 Aug 8.
The evidence on the role of hemodynamics in aorta pathophysiology has yet to be robustly translated into clinical applications, to improve risk stratification of aortic diseases. Motivated by the need to enrich the current understanding of the pathophysiology of the ascending aorta (AAo), this study evaluates in vivo how large-scale aortic flow coherence is affected by AAo dilation and aortic valve phenotype.
A complex networks-based approach is applied to 4D flow MRI data to quantify subject-specific AAo flow coherence in terms of correlation between axial velocity waveforms and the aortic flow rate waveform along the cardiac cycle. The anatomical length of persistence of such correlation is quantified using the recently proposed network metric average weighted curvilinear distance (AWCD). The analysis considers 107 subjects selected to allow an ample stratification in terms of aortic valve morphology, absence/presence of AAo dilation and of aortic valve stenosis.
The analysis highlights that the presence of AAo dilation as well as of bicuspid aortic valve phenotype breaks the physiological AAo flow coherence, quantified in terms of AWCD. Of notice, it emerges that cycle-average blood flow rate and relative AAo dilation are main determinants of AWCD, playing opposite roles in promoting and hampering the persistence of large-scale flow coherence in AAo, respectively.
The findings of this study can contribute to broaden the current mechanistic link between large-scale blood flow coherence and aortic pathophysiology, with the prospect of enriching the existing tools for the in vivo non-invasive hemodynamic risk assessment for aortic diseases onset and progression.
血流动力学在主动脉病理生理学中的作用的证据尚未被强有力地转化为临床应用，以改善主动脉疾病的风险分层。本研究旨在丰富升主动脉（AAo）病理生理学的现有认识，因此从临床实际出发，评估 AAo 扩张和主动脉瓣表型如何影响大规模主动脉血流相干性。
采用基于复杂网络的方法对 4D 流 MRI 数据进行分析，以评估个体的 AAo 血流相干性，具体为沿心动周期的轴向速度波形与主动脉流量波形之间的相关性。使用最近提出的网络度量平均加权曲线距离（AWCD）来量化这种相关性的解剖学长度。该分析考虑了 107 名患者，这些患者在主动脉瓣形态、AAo 扩张的有无以及主动脉瓣狭窄方面有充分的分层。
分析结果表明，AAo 扩张以及二叶式主动脉瓣表型的存在破坏了 AAo 血流相干性，这可以用 AWCD 来衡量。值得注意的是，研究结果表明，平均血流速率和相对 AAo 扩张是 AWCD 的主要决定因素，它们分别促进和阻碍 AAo 中大规模血流相干性的持续性，起到相反的作用。
本研究的结果有助于拓宽血流相干性与主动脉病理生理学之间的现有机制联系，有望丰富现有的主动脉疾病发病和进展的体内非侵入性血流动力学风险评估工具。
