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      A review on low-dimensional physics-based models of systemic arteries: application to estimation of central aortic pressure

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          Abstract

          The physiological processes and mechanisms of an arterial system are complex and subtle. Physics-based models have been proven to be a very useful tool to simulate actual physiological behavior of the arteries. The current physics-based models include high-dimensional models (2D and 3D models) and low-dimensional models (0D, 1D and tube-load models). High-dimensional models can describe the local hemodynamic information of arteries in detail. With regard to an exact model of the whole arterial system, a high-dimensional model is computationally impracticable since the complex geometry, viscosity or elastic properties and complex vectorial output need to be provided. For low-dimensional models, the structure, centerline and viscosity or elastic properties only need to be provided. Therefore, low-dimensional modeling with lower computational costs might be a more applicable approach to represent hemodynamic properties of the entire arterial system and these three types of low-dimensional models have been extensively used in the study of cardiovascular dynamics. In recent decades, application of physics-based models to estimate central aortic pressure has attracted increasing interest. However, to our best knowledge, there has been few review paper about reconstruction of central aortic pressure using these physics-based models. In this paper, three types of low-dimensional physical models (0D, 1D and tube-load models) of systemic arteries are reviewed, the application of three types of models on estimation of central aortic pressure is taken as an example to discuss their advantages and disadvantages, and the proper choice of models for specific researches and applications are advised.

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          Computation of aortic flow from pressure in humans using a nonlinear, three-element model.

          We computed aortic flow pulsations from arterial pressure by simulating a nonlinear, time-varying three-element model of aortic input impedance. The model elements represent aortic characteristic impedance, arterial compliance, and systemic vascular resistance. Parameter values for the first two elements were computed from a published, age-dependent, aortic pressure-area relationship (G. J. Langewouters et al. J. Biomech. 17:425-435, 1984). Peripheral resistance was predicted from mean pressure and model mean flow. Model flow pulsations from aortic pressure showed the visual aspects of an aortic flow curve. For evaluation we compared model mean flow from radial arterial pressure with thermodilution cardiac output estimations, 76 times, in eight open heart surgical patients. The pooled mean difference was +7%, the SD 22%. After using one comparison per patient to calibrate the model, however, we followed quantitative changes in cardiac output that occurred either during changes in the state of the patient or subsequent to vasoactive drugs. The mean deviation from thermodilution cardiac output was +2%, the SD 8%. Given these small errors the method could monitor cardiac output continuously.
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            Mathematical Biofluiddynamics

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              Patient-specific modeling of cardiovascular mechanics.

              Advances in numerical methods and three-dimensional imaging techniques have enabled the quantification of cardiovascular mechanics in subject-specific anatomic and physiologic models. Patient-specific models are being used to guide cell culture and animal experiments and test hypotheses related to the role of biomechanical factors in vascular diseases. Furthermore, biomechanical models based on noninvasive medical imaging could provide invaluable data on the in vivo service environment where cardiovascular devices are employed and on the effect of the devices on physiologic function. Finally, patient-specific modeling has enabled an entirely new application of cardiovascular mechanics, namely predicting outcomes of alternate therapeutic interventions for individual patients. We review methods to create anatomic and physiologic models, obtain properties, assign boundary conditions, and solve the equations governing blood flow and vessel wall dynamics. Applications of patient-specific models of cardiovascular mechanics are presented, followed by a discussion of the challenges and opportunities that lie ahead.
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                Author and article information

                Contributors
                zhoushuranbmie@163.com
                xuls@bmie.neu.edu.cn
                haoll@bmie.neu.edu.cn
                hgxiao@cqut.edu.cn
                yy511721925@163.com
                qilin@bmie.neu.edu.cn
                yaoyudong@mail.neu.edu.cn
                Journal
                Biomed Eng Online
                Biomed Eng Online
                BioMedical Engineering OnLine
                BioMed Central (London )
                1475-925X
                2 April 2019
                2 April 2019
                2019
                : 18
                : 41
                Affiliations
                [1 ]ISNI 0000 0004 0368 6968, GRID grid.412252.2, Sino-Dutch Biomedical and Information Engineering School, , Northeastern University, ; Shenyang, 110819 China
                [2 ]Neusoft Research of Intelligent Healthcare Technology, Co. Ltd., Shenyang, 110167 China
                [3 ]ISNI 0000 0004 1777 9452, GRID grid.411594.c, Chongqing Key Laboratory of Modern Photoelectric Detection Technology and Instrument, School of Optoelectronic Information, , Chongqing University of Technology, ; Chongqing, 400054 China
                Author information
                http://orcid.org/0000-0001-8360-3605
                Article
                660
                10.1186/s12938-019-0660-3
                6446386
                30940144
                7abf36ed-210c-4f4f-b2f4-de8e3b09539a
                © The Author(s) 2019

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                History
                : 1 November 2018
                : 26 March 2019
                Funding
                Funded by: National Natural Science Foundation of China (CN)
                Award ID: 61773110
                Award ID: 61374015
                Award Recipient :
                Funded by: National Natural Science Foundation of China (CN)
                Award ID: 61202258
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/501100001809, National Natural Science Foundation of China;
                Award ID: 61701099
                Award Recipient :
                Funded by: Fundamental Research Funds for the Central Universities
                Award ID: N161904002
                Award ID: N172008008
                Award Recipient :
                Categories
                Review
                Custom metadata
                © The Author(s) 2019

                Biomedical engineering
                physics-based model,systemic arteries,central aortic pressure,0d model,1d model,tube-load model

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