Linking statistical shape models and simulated function in the healthy adult human heart.

Cardiac anatomy plays a crucial role in determining cardiac function. However, there is a poor understanding of how specific and localised anatomical changes affect different cardiac functional outputs. In this work, we test the hypothesis that in a statistical shape model (SSM), the modes that are...

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Main Authors: Cristobal Rodero, Marina Strocchi, Maciej Marciniak, Stefano Longobardi, John Whitaker, Mark D O'Neill, Karli Gillette, Christoph Augustin, Gernot Plank, Edward J Vigmond, Pablo Lamata, Steven A Niederer
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2021-04-01
Series:PLoS Computational Biology
Online Access:https://journals.plos.org/ploscompbiol/article/file?id=10.1371/journal.pcbi.1008851&type=printable
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author Cristobal Rodero
Marina Strocchi
Maciej Marciniak
Stefano Longobardi
John Whitaker
Mark D O'Neill
Karli Gillette
Christoph Augustin
Gernot Plank
Edward J Vigmond
Pablo Lamata
Steven A Niederer
author_facet Cristobal Rodero
Marina Strocchi
Maciej Marciniak
Stefano Longobardi
John Whitaker
Mark D O'Neill
Karli Gillette
Christoph Augustin
Gernot Plank
Edward J Vigmond
Pablo Lamata
Steven A Niederer
author_sort Cristobal Rodero
collection DOAJ
description Cardiac anatomy plays a crucial role in determining cardiac function. However, there is a poor understanding of how specific and localised anatomical changes affect different cardiac functional outputs. In this work, we test the hypothesis that in a statistical shape model (SSM), the modes that are most relevant for describing anatomy are also most important for determining the output of cardiac electromechanics simulations. We made patient-specific four-chamber heart meshes (n = 20) from cardiac CT images in asymptomatic subjects and created a SSM from 19 cases. Nine modes captured 90% of the anatomical variation in the SSM. Functional simulation outputs correlated best with modes 2, 3 and 9 on average (R = 0.49 ± 0.17, 0.37 ± 0.23 and 0.34 ± 0.17 respectively). We performed a global sensitivity analysis to identify the different modes responsible for different simulated electrical and mechanical measures of cardiac function. Modes 2 and 9 were the most important for determining simulated left ventricular mechanics and pressure-derived phenotypes. Mode 2 explained 28.56 ± 16.48% and 25.5 ± 20.85, and mode 9 explained 12.1 ± 8.74% and 13.54 ± 16.91% of the variances of mechanics and pressure-derived phenotypes, respectively. Electrophysiological biomarkers were explained by the interaction of 3 ± 1 modes. In the healthy adult human heart, shape modes that explain large portions of anatomical variance do not explain equivalent levels of electromechanical functional variation. As a result, in cardiac models, representing patient anatomy using a limited number of modes of anatomical variation can cause a loss in accuracy of simulated electromechanical function.
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spelling doaj-art-2d7ba169e8be4c0eb71d0d60f5b652c32025-08-20T03:44:40ZengPublic Library of Science (PLoS)PLoS Computational Biology1553-734X1553-73582021-04-01174e100885110.1371/journal.pcbi.1008851Linking statistical shape models and simulated function in the healthy adult human heart.Cristobal RoderoMarina StrocchiMaciej MarciniakStefano LongobardiJohn WhitakerMark D O'NeillKarli GilletteChristoph AugustinGernot PlankEdward J VigmondPablo LamataSteven A NiedererCardiac anatomy plays a crucial role in determining cardiac function. However, there is a poor understanding of how specific and localised anatomical changes affect different cardiac functional outputs. In this work, we test the hypothesis that in a statistical shape model (SSM), the modes that are most relevant for describing anatomy are also most important for determining the output of cardiac electromechanics simulations. We made patient-specific four-chamber heart meshes (n = 20) from cardiac CT images in asymptomatic subjects and created a SSM from 19 cases. Nine modes captured 90% of the anatomical variation in the SSM. Functional simulation outputs correlated best with modes 2, 3 and 9 on average (R = 0.49 ± 0.17, 0.37 ± 0.23 and 0.34 ± 0.17 respectively). We performed a global sensitivity analysis to identify the different modes responsible for different simulated electrical and mechanical measures of cardiac function. Modes 2 and 9 were the most important for determining simulated left ventricular mechanics and pressure-derived phenotypes. Mode 2 explained 28.56 ± 16.48% and 25.5 ± 20.85, and mode 9 explained 12.1 ± 8.74% and 13.54 ± 16.91% of the variances of mechanics and pressure-derived phenotypes, respectively. Electrophysiological biomarkers were explained by the interaction of 3 ± 1 modes. In the healthy adult human heart, shape modes that explain large portions of anatomical variance do not explain equivalent levels of electromechanical functional variation. As a result, in cardiac models, representing patient anatomy using a limited number of modes of anatomical variation can cause a loss in accuracy of simulated electromechanical function.https://journals.plos.org/ploscompbiol/article/file?id=10.1371/journal.pcbi.1008851&type=printable
spellingShingle Cristobal Rodero
Marina Strocchi
Maciej Marciniak
Stefano Longobardi
John Whitaker
Mark D O'Neill
Karli Gillette
Christoph Augustin
Gernot Plank
Edward J Vigmond
Pablo Lamata
Steven A Niederer
Linking statistical shape models and simulated function in the healthy adult human heart.
PLoS Computational Biology
title Linking statistical shape models and simulated function in the healthy adult human heart.
title_full Linking statistical shape models and simulated function in the healthy adult human heart.
title_fullStr Linking statistical shape models and simulated function in the healthy adult human heart.
title_full_unstemmed Linking statistical shape models and simulated function in the healthy adult human heart.
title_short Linking statistical shape models and simulated function in the healthy adult human heart.
title_sort linking statistical shape models and simulated function in the healthy adult human heart
url https://journals.plos.org/ploscompbiol/article/file?id=10.1371/journal.pcbi.1008851&type=printable
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