Literature DB >> 33662019

Multimodal cardiovascular model for hemodynamic analysis: Simulation study on mitral valve disorders.

Dibyendu Roy1, Oishee Mazumder1, Aniruddha Sinha1, Sundeep Khandelwal1.   

Abstract

Valvular heart diseases are a prevalent cause of cardiovascular morbidity and mortality worldwide, affecting a wide spectrum of the population. In-silico modeling of the cardiovascular system has recently gained recognition as a useful tool in cardiovascular research and clinical applications. Here, we present an in-silico cardiac computational model to analyze the effect and severity of valvular disease on general hemodynamic parameters. We propose a multimodal and multiscale cardiovascular model to simulate and understand the progression of valvular disease associated with the mitral valve. The developed model integrates cardiac electrophysiology with hemodynamic modeling, thus giving a broader and holistic understanding of the effect of disease progression on various parameters like ejection fraction, cardiac output, blood pressure, etc., to assess the severity of mitral valve disorders, naming Mitral Stenosis and Mitral Regurgitation. The model mimics an adult cardiovascular system, comprising a four-chambered heart with systemic, pulmonic circulation. The simulation of the model output comprises regulated pressure, volume, and flow for each heart chamber, valve dynamics, and Photoplethysmogram signal for normal physiological as well as pathological conditions due to mitral valve disorders. The generated physiological parameters are in agreement with published data. Additionally, we have related the simulated left atrium and ventricle dimensions, with the enlargement and hypertrophy in the cardiac chambers of patients with mitral valve disorders, using their Electrocardiogram available in Physionet PTBI dataset. The model also helps to create 'what if' scenarios and relevant analysis to study the effect in different hemodynamic parameters for stress or exercise like conditions.

Entities:  

Year:  2021        PMID: 33662019      PMCID: PMC7932118          DOI: 10.1371/journal.pone.0247921

Source DB:  PubMed          Journal:  PLoS One        ISSN: 1932-6203            Impact factor:   3.240


  47 in total

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Authors:  Borys Surawicz; Rory Childers; Barbara J Deal; Leonard S Gettes; James J Bailey; Anton Gorgels; E William Hancock; Mark Josephson; Paul Kligfield; Jan A Kors; Peter Macfarlane; Jay W Mason; David M Mirvis; Peter Okin; Olle Pahlm; Pentti M Rautaharju; Gerard van Herpen; Galen S Wagner; Hein Wellens
Journal:  Circulation       Date:  2009-02-19       Impact factor: 29.690

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6.  Image-based modeling of hemodynamics in coronary artery aneurysms caused by Kawasaki disease.

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8.  Synthetic PPG generation from haemodynamic model with baroreflex autoregulation: a Digital twin of cardiovascular system.

Authors:  Oishee Mazumder; Dibyendu Roy; Sakyajit Bhattacharya; Aniruddha Sinha; Arpan Pal
Journal:  Conf Proc IEEE Eng Med Biol Soc       Date:  2019-07

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Journal:  Biomed Eng Online       Date:  2015-04-17       Impact factor: 2.819

10.  Automated and Interpretable Patient ECG Profiles for Disease Detection, Tracking, and Discovery.

Authors:  Geoffrey H Tison; Jeffrey Zhang; Francesca N Delling; Rahul C Deo
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  2 in total

1.  An Investigation of Left Ventricular Valve Disorders and the Mechano-Electric Feedback Using a Synergistic Lumped Parameter Cardiovascular Numerical Model.

Authors:  Nicholas Pearce; Eun-Jin Kim
Journal:  Bioengineering (Basel)       Date:  2022-09-08

2.  Computational Model for Therapy Optimization of Wearable Cardioverter Defibrillator: Shockable Rhythm Detection and Optimal Electrotherapy.

Authors:  Oishee Mazumder; Rohan Banerjee; Dibyendu Roy; Ayan Mukherjee; Avik Ghose; Sundeep Khandelwal; Aniruddha Sinha
Journal:  Front Physiol       Date:  2021-12-10       Impact factor: 4.566

  2 in total

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