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Modeling left ventricular diastolic dysfunction: classification and key indicators
BACKGROUND: Mathematical modeling can be employed to overcome the practical difficulty of isolating the mechanisms responsible for clinical heart failure in the setting of normal left ventricular ejection fraction (HFNEF). In a human cardiovascular respiratory system (H-CRS) model we introduce three...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2011
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3117805/ https://www.ncbi.nlm.nih.gov/pubmed/21554684 http://dx.doi.org/10.1186/1742-4682-8-14 |
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author | Luo, Chuan Ramachandran, Deepa Ware, David L Ma, Tony S Clark, John W |
author_facet | Luo, Chuan Ramachandran, Deepa Ware, David L Ma, Tony S Clark, John W |
author_sort | Luo, Chuan |
collection | PubMed |
description | BACKGROUND: Mathematical modeling can be employed to overcome the practical difficulty of isolating the mechanisms responsible for clinical heart failure in the setting of normal left ventricular ejection fraction (HFNEF). In a human cardiovascular respiratory system (H-CRS) model we introduce three cases of left ventricular diastolic dysfunction (LVDD): (1) impaired left ventricular active relaxation (IR-type); (2) increased passive stiffness (restrictive or R-type); and (3) the combination of both (pseudo-normal or PN-type), to produce HFNEF. The effects of increasing systolic contractility are also considered. Model results showing ensuing heart failure and mechanisms involved are reported. METHODS: We employ our previously described H-CRS model with modified pulmonary compliances to better mimic normal pulmonary blood distribution. IR-type is modeled by changing the activation function of the left ventricle (LV), and R-type by increasing diastolic stiffness of the LV wall and septum. A 5(th)-order Cash-Karp Runge-Kutta numerical integration method solves the model differential equations. RESULTS: IR-type and R-type decrease LV stroke volume, cardiac output, ejection fraction (EF), and mean systemic arterial pressure. Heart rate, pulmonary pressures, pulmonary volumes, and pulmonary and systemic arterial-venous O(2 )and CO(2 )differences increase. IR-type decreases, but R-type increases the mitral E/A ratio. PN-type produces the well-described, pseudo-normal mitral inflow pattern. All three types of LVDD reduce right ventricular (RV) and LV EF, but the latter remains normal or near normal. Simulations show reduced EF is partly restored by an accompanying increase in systolic stiffness, a compensatory mechanism that may lead clinicians to miss the presence of HF if they only consider LVEF and other indices of LV function. Simulations using the H-CRS model indicate that changes in RV function might well be diagnostic. This study also highlights the importance of septal mechanics in LVDD. CONCLUSION: The model demonstrates that abnormal LV diastolic performance alone can result in decreased LV and RV systolic performance, not previously appreciated, and contribute to the clinical syndrome of HF. Furthermore, alterations of RV diastolic performance are present and may be a hallmark of LV diastolic parameter changes that can be used for better clinical recognition of LV diastolic heart disease. |
format | Online Article Text |
id | pubmed-3117805 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2011 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-31178052011-06-18 Modeling left ventricular diastolic dysfunction: classification and key indicators Luo, Chuan Ramachandran, Deepa Ware, David L Ma, Tony S Clark, John W Theor Biol Med Model Research BACKGROUND: Mathematical modeling can be employed to overcome the practical difficulty of isolating the mechanisms responsible for clinical heart failure in the setting of normal left ventricular ejection fraction (HFNEF). In a human cardiovascular respiratory system (H-CRS) model we introduce three cases of left ventricular diastolic dysfunction (LVDD): (1) impaired left ventricular active relaxation (IR-type); (2) increased passive stiffness (restrictive or R-type); and (3) the combination of both (pseudo-normal or PN-type), to produce HFNEF. The effects of increasing systolic contractility are also considered. Model results showing ensuing heart failure and mechanisms involved are reported. METHODS: We employ our previously described H-CRS model with modified pulmonary compliances to better mimic normal pulmonary blood distribution. IR-type is modeled by changing the activation function of the left ventricle (LV), and R-type by increasing diastolic stiffness of the LV wall and septum. A 5(th)-order Cash-Karp Runge-Kutta numerical integration method solves the model differential equations. RESULTS: IR-type and R-type decrease LV stroke volume, cardiac output, ejection fraction (EF), and mean systemic arterial pressure. Heart rate, pulmonary pressures, pulmonary volumes, and pulmonary and systemic arterial-venous O(2 )and CO(2 )differences increase. IR-type decreases, but R-type increases the mitral E/A ratio. PN-type produces the well-described, pseudo-normal mitral inflow pattern. All three types of LVDD reduce right ventricular (RV) and LV EF, but the latter remains normal or near normal. Simulations show reduced EF is partly restored by an accompanying increase in systolic stiffness, a compensatory mechanism that may lead clinicians to miss the presence of HF if they only consider LVEF and other indices of LV function. Simulations using the H-CRS model indicate that changes in RV function might well be diagnostic. This study also highlights the importance of septal mechanics in LVDD. CONCLUSION: The model demonstrates that abnormal LV diastolic performance alone can result in decreased LV and RV systolic performance, not previously appreciated, and contribute to the clinical syndrome of HF. Furthermore, alterations of RV diastolic performance are present and may be a hallmark of LV diastolic parameter changes that can be used for better clinical recognition of LV diastolic heart disease. BioMed Central 2011-05-09 /pmc/articles/PMC3117805/ /pubmed/21554684 http://dx.doi.org/10.1186/1742-4682-8-14 Text en Copyright ©2011 Luo et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Luo, Chuan Ramachandran, Deepa Ware, David L Ma, Tony S Clark, John W Modeling left ventricular diastolic dysfunction: classification and key indicators |
title | Modeling left ventricular diastolic dysfunction: classification and key indicators |
title_full | Modeling left ventricular diastolic dysfunction: classification and key indicators |
title_fullStr | Modeling left ventricular diastolic dysfunction: classification and key indicators |
title_full_unstemmed | Modeling left ventricular diastolic dysfunction: classification and key indicators |
title_short | Modeling left ventricular diastolic dysfunction: classification and key indicators |
title_sort | modeling left ventricular diastolic dysfunction: classification and key indicators |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3117805/ https://www.ncbi.nlm.nih.gov/pubmed/21554684 http://dx.doi.org/10.1186/1742-4682-8-14 |
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