Network-Based Characterization of Blood Large-Scale Coherent Motion in the Healthy Human Aorta with 4D Flow MRI
Objective: The need for distilling the hemodynamic complexity into clinically relevant quantities has imposed a reductionist approach to investigate aortic flows, resulting in a lossy compression of the information hidden in 4D aortic fluid structures. Aiming at reducing information loss, this study proposes a network-based approach to identify and characterize in vivo the large-scale coherent motion of blood in the healthy human aorta using 4D Flow MRI. Methods: Adopting the quantitative paradigm of the aortic flow as a “social network”, 4D flow MRI acquisitions were performed on forty-one healthy volunteers. Correlations between the aortic blood flow rate waveform at the proximal ascending aorta (AAo), assumed as a main determinant of the aortic flow, and the waveforms of the axial velocity (aligned with the aortic centerline) in the whole aorta were used to build “one-to-all” networks. The impact of the driving flow rate waveform and of the main aortic geometric attributes on the transport of large-scale coherent fluid structures was investigated. Results: The anatomical length of persistence of large-scale coherent motion was the 29.6% of the healthy thoracic aorta length (median value, IQR 23.1%-33.9%). Moreover, it was positively correlated with the average and peak-to-peak AAo blood flow rate values, suggesting a remarkable inertial effect of the AAo flow rate on aortic hemodynamic coherence. No association emerged between the anatomical length of persistence and aortic geometric attributes. Conclusion: The here proposed in vivo approach allowed to quantitatively characterize the large-scale aortic blood motion, strengthening the definition of coherent hemodynamic structures. Significance: The findings on healthy aortas may be used as reference values to investigate the impact of aortic disease or devices implantation in disrupting/restoring the physiological spatiotemporal coherence of large-scale aortic flow.
Email Address of Submitting Authorkarol.email@example.com
ORCID of Submitting Author0000-0002-6935-4021
Submitting Author's InstitutionPolitoBIOMed Lab, Department of Mechanical and Aerospace Engineering, Politecnico di Torino, Turin, Italy
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