The Role of Myocardial Fiber Direction in Epicardial Activation Patterns via Uncertainty Quantification.


Journal

Computing in cardiology
ISSN: 2325-8861
Titre abrégé: Comput Cardiol (2010)
Pays: United States
ID NLM: 101562329

Informations de publication

Date de publication:
Sep 2021
Historique:
entrez: 22 4 2022
pubmed: 23 4 2022
medline: 23 4 2022
Statut: ppublish

Résumé

Fiber structure governs the spread of excitation in the heart; however, little is known about the effects of physiological variability in fiber orientation on epicardial activation. To investigate these effects, we implemented ventricular simulations of activation using rule-based fiber orientations, and robust uncertainty quantification algorithms to capture detailed maps of model sensitivity. Specifically, we implemented polynomial chaos expansion, which allows for robust exploration with reduced computational demand through an emulator function to approximate the underlying forward model. We applied these techniques to examine the activation sequence of the heart in response to both epicardial and endocardial stimuli within the left ventricular free wall and variations in fiber orientation. Our results showed that physiological variation in fiber orientation does not significantly impact the location of activation features, but it does impact the overall spread of activation. Future studies will investigate under which circumstances physiological changes in fiber orientation might alter electrical propagation such that the resulting simulations produce misleading outcomes.

Identifiants

pubmed: 35449765
doi: 10.23919/cinc53138.2021.9662950
pmc: PMC9020927
mid: NIHMS1796971
doi:

Types de publication

Journal Article

Langues

eng

Subventions

Organisme : NIGMS NIH HHS
ID : R24 GM136986
Pays : United States
Organisme : NIBIB NIH HHS
ID : U24 EB029012
Pays : United States

Références

Physiol Meas. 2020 Feb 05;41(1):015002
pubmed: 31860892
SoftwareX. 2020 Jan-Jun;11:100454
pubmed: 32607406
IEEE Trans Biomed Eng. 1998 Apr;45(4):449-62
pubmed: 9556962
Math Biosci. 1998 Jan 15;147(2):131-71
pubmed: 9433061
Med Image Anal. 2021 Jul;71:102080
pubmed: 33975097
Med Image Anal. 2018 Apr;45:83-93
pubmed: 29414438
Prog Biophys Mol Biol. 2008 Jan-Apr;96(1-3):3-18
pubmed: 17900668
J Comput Phys. 2017 Oct 1;346:191-211
pubmed: 28819329
IEEE Trans Med Imaging. 2012 Jul;31(7):1436-47
pubmed: 22481815
Ann Biomed Eng. 2012 Oct;40(10):2243-54
pubmed: 22648575

Auteurs

Lindsay C Rupp (LC)

Scientific Computing and Imaging Institute, University of Utah, SLC, UT, USA.
Nora Eccles Cardiovascular Research and Training Institute, University of Utah, SLC, UT, USA.
Department of Biomedical Engineering, University of Utah, SLC, UT, USA.

Jake A Bergquist (JA)

Scientific Computing and Imaging Institute, University of Utah, SLC, UT, USA.
Nora Eccles Cardiovascular Research and Training Institute, University of Utah, SLC, UT, USA.
Department of Biomedical Engineering, University of Utah, SLC, UT, USA.

Brian Zenger (B)

Scientific Computing and Imaging Institute, University of Utah, SLC, UT, USA.
Nora Eccles Cardiovascular Research and Training Institute, University of Utah, SLC, UT, USA.
Department of Biomedical Engineering, University of Utah, SLC, UT, USA.
School of Medicine, University of Utah, SLC, UT, USA.

Karli Gillette (K)

Institute of Biophysics, Medical University of Graz, Graz, Austria.

Akil Narayan (A)

Scientific Computing and Imaging Institute, University of Utah, SLC, UT, USA.

Jess D Tate (JD)

Scientific Computing and Imaging Institute, University of Utah, SLC, UT, USA.

Gernot Plank (G)

Institute of Biophysics, Medical University of Graz, Graz, Austria.

Rob S MacLeod (RS)

Scientific Computing and Imaging Institute, University of Utah, SLC, UT, USA.
Nora Eccles Cardiovascular Research and Training Institute, University of Utah, SLC, UT, USA.
Department of Biomedical Engineering, University of Utah, SLC, UT, USA.

Classifications MeSH