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Cited by 19Cardiac Imaging and DiagnosticsElasticity and Material ModelingAnatomy and Medical Technology

An introductory overview of image-based computational modeling in personalized cardiovascular medicine.

Open access
Nguyen, Thanh Danh, Kadri, Olufemi E., Voronov, Roman S.·2020·Frontiers in Bioengineering and Biotechnology
DOI 10.3389/fbioe.2020.529365PMC PMC7546862
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Abstract

Cardiovascular diseases account for the number one cause of deaths in the world. Part of the reason for such grim statistics is our limited understanding of the underlying mechanisms causing these devastating pathologies, which is made difficult by the invasiveness of the procedures associated with their diagnosis (e.g., inserting catheters into the coronal artery to measure blood flow to the heart). Likewise, it is also difficult to design and test assistive devices without implanting them in vivo. However, with the recent advancements made in biomedical scanning technologies and computer simulations, image-based modeling (IBM) has arisen as the next logical step in the evolution of non-invasive patient-specific cardiovascular medicine. Yet, due to its novelty, it is still relatively unknown outside of the niche field. Therefore, the goal of this manuscript is to review the current state-of-the-art and the limitations of the methods used in this area of research, as well as their applications to personalized cardiovascular investigations and treatments. Specifically, the modeling of three different physics – electrophysiology, biomechanics and hemodynamics - used in the cardiovascular IBM is discussed in the context of the physiology that each one of them describes and the mechanisms of the underlying cardiac diseases that they can provide insight into. Only the “bare-bones” of the modeling approaches are discussed in order to make this introductory material more accessible to an outside observer. Additionally, the imaging methods, the aspects of the unique cardiac anatomy derived from them, and their relation to the modeling algorithms are reviewed. Finally, conclusions are drawn about the future evolution of these methods and their potential towards revolutionizing the non-invasive diagnosis, virtual design of treatments / assistive devices, and increasing our understanding of these lethal cardiovascular diseases.

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  • When imaging data is noisy, an alternative rule-based methodology can be utilized to simulate electrical wave propagation and mechanical contraction in the heart.

    “However, when imaging data is noisy, an alternative rule-based methodology can be utilized to simulate electrical wave propagation and mechanical contraction in the heart (Bayer et al., 2012; Lopez-Perez et al., 2015; Nguyen et al., 2020).”

    From Thoroughly Calibrated Modular Agent-Based Model of the Human Cardiovascular and Renal Systems for Blood Pressure Regulation in Health and Disease (2021) · cites this paper as Nguyen et al., 2020

    The Geometry Module’s “Rule-Based Heuristics” section describes rule-based estimates of myocardial fiber orientation as an alternative when microstructural details are difficult to image in a beating heart. The paper links fiber structure to both electrical conduction and mechanical contraction, but it does not specifically identify noisy imaging data as the reason to use the rule-based approach; its Imaging-to-Modeling Pipeline section instead discusses reducing image noise through post-processing. Page numbers were not available in our copy. (LLM, conf=0.83)

    Experimental — accuracy not yet measured

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Cited by

Sorted by citations

Authors
Nguyen, T. D., Kadri, O. E., & Voronov, R. S.
Affiliations
New Jersey Institute of Technology (US)
Corresponding author
Voronov, Roman S.
ORCID
Venue
Frontiers in Bioengineering and Biotechnology
Publisher
Frontiers Media SA
Published
2020-09-25
Volume
8
Pages
529365-529365
ISSN
2296-4185 (ISSN-L)
DOI
10.3389/fbioe.2020.529365
PMC
PMC7546862
OpenAlex
W3088135601
Cited by
19
References
3
Citations by year
2026: 3 · 2025: 1 · 2024: 6 · 2023: 3 · 2022: 3 · 2021: 3
FWCI
0.33
Type
journal article
Language
en
Open access
Licence
Locations
  • Frontiers in Bioengineering and Biotechnology (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Funders
  • New Jersey Health Foundation
  • Gustavus and Louise Pfeiffer Research Foundation
Topics
  • Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Cardiac Imaging and Diagnostics
  • Physical Sciences › Engineering › Biomedical Engineering › Elasticity and Material Modeling
  • Physical Sciences › Engineering › Biomedical Engineering › Anatomy and Medical Technology
Keywords
image-based modeling, patient-specific cardiac modeling, cardiac electrophysiology, cardiac biomechanics, hemodynamics, cardiac imaging, cardiac anatomy, non-invasive diagnosis, assistive devices, cardiovascular disease

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