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The Critical Role of Lumped Parameter Models in Patient-Specific Cardiovascular Simulations

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Abstract

Cardiovascular (CV) disease impacts tens of millions of people annually and carries a massive global economic burden. Continued advances in medical imaging, hardware and computational efficiency are leading to an increased interest in the field of cardiovascular computational modelling to help combat the devastating impact of CV disease. This review article will focus on a computational modelling technique known as lumped parameter modelling (LPM). Due to its rapid computation time, ease of automation and relative simplicity, LPM holds the potential of aiding in the early diagnosis of CV disease, assisting clinicians in determining personalized and optimal treatments and offering a unique in-silico setting to study cardiac and circulatory diseases. In addition, it is one of the many tools that are needed in the eventual development of patient specific cardiovascular “digital twin” frameworks. This review focuses on how the personalization of cardiovascular lumped parameter models are beginning to impact the field of patient specific cardiovascular care. It presents an in-depth examination of the approaches used to develop current predictive LPM hemodynamic frameworks as well as their applications within the realm of cardiovascular disease. The roles of these models in higher order blood flow (1D/3D) simulations are also explored in addition to the different algorithms used to personalize the models. The article outlines the future directions of this field and the current challenges and opportunities related to the translation of this technology into clinical settings.

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source software Sim Vascular [177]; b Open and closed loop 0D boundary conditions applied to 3D models from within the Sim Vascular software [177]

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Funding

This work was supported by NSERC Discovery Grant (RGPIN-2017-05349) and NSERC CRD Grant (CRDPJ 537352 – 18). NSERC (https://www.nserc-crsng.gc.ca/index_eng.asp) as the funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

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  1. School of Biomedical Engineering, McMaster University, Hamilton, ON, Canada

    Louis Garber & Zahra Keshavarz-Motamed

  2. Department of Mechanical Engineering, McMaster University, Hamilton, ON, L8S 4L7, Canada

    Seyedvahid Khodaei & Zahra Keshavarz-Motamed

  3. School of Computational Science and Engineering, McMaster University, Hamilton, ON, Canada

    Zahra Keshavarz-Motamed

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  1. Louis Garber
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  2. Seyedvahid Khodaei
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LG: Literature analysis and investigation, original draft manuscript writing and visualization, SK: Reviewing and editing, ZK-M: Conception, design of literature classification, critical revision and final approval of the manuscript.

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Correspondence to Zahra Keshavarz-Motamed.

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Garber, L., Khodaei, S. & Keshavarz-Motamed, Z. The Critical Role of Lumped Parameter Models in Patient-Specific Cardiovascular Simulations. Arch Computat Methods Eng 29, 2977–3000 (2022). https://doi.org/10.1007/s11831-021-09685-5

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