In recent years, several works have addressed the problem of modeling blood flow phenomena in veins, as a response to increasing interest in modeling pathological conditions occurring in the venous network and their connection with the rest of the circulatory system. In this context, one-dimensional models have proven to be extremely efficient in delivering predictions in agreement with in-vivo observations. Pursuing the increase of anatomical accuracy and its connection to physiological principles in haemodynamics simulations, the main aim of this work is to describe a novel closed-loop Anatomically-Detailed Arterial-Venous Network (ADAVN) model. An extremely refined description of the arterial network consisting of 2,185 arterial vessels is coupled to a novel venous network featuring high level of anatomical detail in cerebral and coronary vascular territories. The entire venous network comprises 189 venous vessels, 79 of which drain the brain and 14 are coronary veins. Fundamental physiological mechanisms accounting for the interaction of brain blood flow with the cerebrospinal fluid and of the coronary circulation with the cardiac mechanics are considered. Several issues related to the coupling of arterial and venous vessels at the microcirculation level are discussed in detail. Numerical simulations are compared to patient records published in the literature to show the descriptive capabilities of the model. Furthermore, a local sensitivity analysis is performed, evidencing the high impact of the venous circulation on main cardiovascular variables.

An Anatomically Detailed Arterial-Venous Network Model. Cerebral and Coronary Circulation / Muller, Lucas O.; Watanabe, Sansuke M.; Toro, Eleuterio F.; Feijóo, Raúl A.; Blanco, Pablo J.. - In: FRONTIERS IN PHYSIOLOGY. - ISSN 1664-042X. - 2023, 14:(2023), pp. 1-19. [10.3389/fphys.2023.1162391]

An Anatomically Detailed Arterial-Venous Network Model. Cerebral and Coronary Circulation

Muller, Lucas O.;Toro, Eleuterio F.;
2023-01-01

Abstract

In recent years, several works have addressed the problem of modeling blood flow phenomena in veins, as a response to increasing interest in modeling pathological conditions occurring in the venous network and their connection with the rest of the circulatory system. In this context, one-dimensional models have proven to be extremely efficient in delivering predictions in agreement with in-vivo observations. Pursuing the increase of anatomical accuracy and its connection to physiological principles in haemodynamics simulations, the main aim of this work is to describe a novel closed-loop Anatomically-Detailed Arterial-Venous Network (ADAVN) model. An extremely refined description of the arterial network consisting of 2,185 arterial vessels is coupled to a novel venous network featuring high level of anatomical detail in cerebral and coronary vascular territories. The entire venous network comprises 189 venous vessels, 79 of which drain the brain and 14 are coronary veins. Fundamental physiological mechanisms accounting for the interaction of brain blood flow with the cerebrospinal fluid and of the coronary circulation with the cardiac mechanics are considered. Several issues related to the coupling of arterial and venous vessels at the microcirculation level are discussed in detail. Numerical simulations are compared to patient records published in the literature to show the descriptive capabilities of the model. Furthermore, a local sensitivity analysis is performed, evidencing the high impact of the venous circulation on main cardiovascular variables.
2023
Muller, Lucas O.; Watanabe, Sansuke M.; Toro, Eleuterio F.; Feijóo, Raúl A.; Blanco, Pablo J.
An Anatomically Detailed Arterial-Venous Network Model. Cerebral and Coronary Circulation / Muller, Lucas O.; Watanabe, Sansuke M.; Toro, Eleuterio F.; Feijóo, Raúl A.; Blanco, Pablo J.. - In: FRONTIERS IN PHYSIOLOGY. - ISSN 1664-042X. - 2023, 14:(2023), pp. 1-19. [10.3389/fphys.2023.1162391]
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11572/383169
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