An Introductory Overview of Image-Based Computational Modeling in Personalized Cardiovascular Medicine

Nguyen, Thanh-Danh; Kadri, Olufemi E.; Voronov, Roman S.

doi:10.3389/fbioe.2020.529365

Cited by 12 publications

(14 citation statements)

References 141 publications

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“…To personalize the cardiac parameters of the model, it is possible to use data obtained from clinical imaging. 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 ). Application of this methodology can be useful for extension the model to involve the personalized anatomy of the heart.…”

Section: Discussionmentioning

confidence: 99%

Thoroughly Calibrated Modular Agent-Based Model of the Human Cardiovascular and Renal Systems for Blood Pressure Regulation in Health and Disease

et al. 2021

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Here we present a modular agent-based mathematical model of the human cardiovascular and renal systems. It integrates the previous models primarily developed by A. C. Guyton, F. Karaaslan, K. M. Hallow, and Y. V. Solodyannikov. We performed the model calibration to find an equilibrium state within the normal vital sign ranges for a healthy adult. We verified the model’s abilities to reproduce equilibrium states with abnormal physiological values related to different combinations of cardiovascular diseases (such as systemic hypertension, chronic heart failure, pulmonary hypertension, etc.). For the model creation and validation, we involved over 200 scientific studies covering known models of the human cardiovascular and renal functions, biosimulation platforms, and clinical measurements of physiological quantities in normal and pathological conditions. We compiled detailed documentation describing all equations, parameters and variables of the model with justification of all formulas and values. The model is implemented in BioUML and available in the web-version of the software.

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Section: Discussionmentioning

confidence: 99%

Thoroughly Calibrated Modular Agent-Based Model of the Human Cardiovascular and Renal Systems for Blood Pressure Regulation in Health and Disease

et al. 2021

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“…Efficient and accurate personalization of computational models is widely recognized as the crucial next step for the successful translation of simulation technology into clinical applications (Corral‐Acero et al, 2020; Hose et al, 2019; Morris et al, 2016; Nguyen et al, 2020; Safaei et al, 2016; Van Laere et al, 2018). Model personalization involves the definition of two groups of parameters that determine the function of the mathematical model.…”

Section: Model Customization and Parameter Estimationmentioning

confidence: 99%

“…These are geometric parameters determined by cardiovascular anatomy and physiological parameters determined by cardiovascular function. For geometric (anatomical) personalization, models may be parameterized using patient‐specific cardiovascular geometry (vessel length and radius) extracted from medical imaging (ultrasound, CT, or MRI)—also referred to as image‐based modeling (Nguyen et al, 2020). A few geometric parameters (e.g., vessel thickness) can be computed by allometric laws where technical challenges preclude their acquisition (vessels too small to be seen, time required for image acquisition too long, or inaccessibility).…”

Section: Model Customization and Parameter Estimationmentioning

confidence: 99%

From fetus to neonate: A review of cardiovascular modeling in early life

May

Talou

Clark

et al. 2023

WIREs Mechanisms of Disease

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Computational modeling has well‐established utility in the study of cardiovascular hemodynamics, with applications in medical research and, increasingly, in clinical settings to improve the diagnosis and treatment of cardiovascular diseases. Most cardiovascular models developed to date have been of the adult circulatory system; however, the perinatal period is unique as cardiovascular physiology undergoes drastic changes from the fetal circulation, during the birth transition, and into neonatal life. There may also be further complications in this period: for example, preterm birth (defined as birth before 37 completed weeks of gestation) carries risks of short‐term cardiovascular instability and is associated with increased lifetime cardiovascular risk. Here, we review computational models of the cardiovascular system in early life, their applications to date and potential improvements and enhancements of these models. We propose a roadmap for developing an open‐source cardiovascular model that spans the fetal, perinatal, and postnatal periods. This article is categorized under: Cardiovascular Diseases > Computational Models Cardiovascular Diseases > Biomedical Engineering Congenital Diseases > Computational Models

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“…1 ). However, the complexity and variability of image data as well as the lack of ground truth, mean that image processing is inherently challenging ( Nguyen et al, 2020 ).…”

Section: Image Processingmentioning

confidence: 99%

Challenges and opportunities of integrating imaging and mathematical modelling to interrogate biological processes

Berg¹,

Holroyd²,

Walsh³

et al. 2022

The International Journal of Biochemistry & Cell Biology

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An Introductory Overview of Image-Based Computational Modeling in Personalized Cardiovascular Medicine

Cited by 12 publications

References 141 publications

Thoroughly Calibrated Modular Agent-Based Model of the Human Cardiovascular and Renal Systems for Blood Pressure Regulation in Health and Disease

Thoroughly Calibrated Modular Agent-Based Model of the Human Cardiovascular and Renal Systems for Blood Pressure Regulation in Health and Disease

From fetus to neonate: A review of cardiovascular modeling in early life

Challenges and opportunities of integrating imaging and mathematical modelling to interrogate biological processes

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