Institut Català de la Salut
[Calò K, Gallo D, Scarsoglio S, Ridolfi L] PolitoBIOMed Lab, Department of Mechanical and Aerospace Engineering, Politecnico di Torino, 10129 Turin, Italy. [Guala A] Vall d’Hebron Institut de Recerca (VHIR), Barcelona, Spain. CIBER-CV, Instituto de Salud Carlos III (ISCIII), Madrid, Spain. [Rodriguez Palomares J] Vall d’Hebron Institut de Recerca (VHIR), Barcelona, Spain. CIBER-CV, Instituto de Salud Carlos III (ISCIII), Madrid, Spain. Servei de Cardiologia, Vall d’Hebron Hospital Universitari, Barcelona, Spain
Vall d'Hebron Barcelona Hospital Campus
2022-02-22T07:22:00Z
2022-02-22T07:22:00Z
2021-09
Dilatació aòrtica; Aneurisma de l'aorta ascendent; Anàlisi espai-temporal
Dilatación aórtica; Aneurisma de la aorta ascendente; Análisis espacio-temporal
Aortic dilation; Ascending aorta aneurysm; Spatiotemporal analysis
Motivated by the evidence that the onset and progression of the aneurysm of the ascending aorta (AAo) is intertwined with an adverse hemodynamic environment, the present study characterized in vivo the hemodynamic spatiotemporal complexity and organization in human aortas, with and without dilated AAo, exploring the relations with clinically relevant hemodynamic and geometric parameters. The Complex Networks (CNs) theory was applied for the first time to 4D flow magnetic resonance imaging (MRI) velocity data of ten patients, five of them presenting with AAo dilation. The time-histories along the cardiac cycle of velocity-based quantities were used to build correlation-based CNs. The CNs approach succeeded in capturing large-scale coherent flow features, delimiting flow separation and recirculation regions. CNs metrics highlighted that an increasing AAo dilation (expressed in terms of the ratio between the maximum AAo and aortic root diameter) disrupts the correlation in forward flow reducing the correlation persistence length, while preserving the spatiotemporal homogeneity of secondary flows. The application of CNs to in vivo 4D MRI data holds promise for a mechanistic understanding of the spatiotemporal complexity and organization of aortic flows, opening possibilities for the integration of in vivo quantitative hemodynamic information into risk stratification and classification criteria.
Open access funding provided by Politecnico di Torino within the CRUI-CARE Agreement.
Article
Published version
English
Aorta - Imatgeria; Imatgeria per al diagnòstic; Hemodinàmica; PHENOMENA AND PROCESSES::Circulatory and Respiratory Physiological Phenomena::Cardiovascular Physiological Phenomena::Hemodynamics; ANALYTICAL, DIAGNOSTIC AND THERAPEUTIC TECHNIQUES, AND EQUIPMENT::Diagnosis::Diagnostic Techniques and Procedures::Diagnostic Imaging::Tomography::Magnetic Resonance Imaging; ANATOMY::Cardiovascular System::Blood Vessels::Arteries::Aorta; Other subheadings::Other subheadings::Other subheadings::/diagnostic imaging; FENÓMENOS Y PROCESOS::fenómenos fisiológicos respiratorios y circulatorios::fenómenos fisiológicos cardiovasculares::hemodinámica; TÉCNICAS Y EQUIPOS ANALÍTICOS, DIAGNÓSTICOS Y TERAPÉUTICOS::diagnóstico::técnicas y procedimientos diagnósticos::diagnóstico por imagen::tomografía::imagen por resonancia magnética; ANATOMÍA::sistema cardiovascular::vasos sanguíneos::arterias::aorta; Otros calificadores::Otros calificadores::Otros calificadores::/diagnóstico por imagen
Springer
Annals of Biomedical Engineering;49(9)
https://doi.org/10.1007/s10439-021-02798-9
Attribution 4.0 International
http://creativecommons.org/licenses/by/4.0/
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