Estimation of pulmonary vascular resistance for Glenn physiology.


Journal

PloS one
ISSN: 1932-6203
Titre abrégé: PLoS One
Pays: United States
ID NLM: 101285081

Informations de publication

Date de publication:
2024
Historique:
received: 18 04 2024
accepted: 12 07 2024
medline: 26 7 2024
pubmed: 26 7 2024
entrez: 26 7 2024
Statut: epublish

Résumé

Children with single ventricle heart disease typically require a series of three operations, (1) Norwood, (2) Glenn, and (3) Fontan, which ultimately results in complete separation of the pulmonary and systemic circuits to improve pulmonary/systemic circulation. In the last stage, the Fontan operation, the inferior vena cava (IVC) is connected to the pulmonary arteries (PAs), allowing the remainder of deoxygenated blood to passively flow to the pulmonary circuit. It is hypothesized that optimizing the Fontan anatomy would lead to decreased power loss and more balanced hepatic flow distribution. One approach to optimizing the geometry is to create a patient-specific digital twin to simulate various configurations of the Fontan conduit, which requires a computational model of the proximal PA anatomy and resistance, as well as the distal Pulmonary Vascular Resistance (PVR), at the Glenn stage. To that end, an optimization pipeline was developed using 3D computational fluid dynamics (CFD) and 0D lumped parameter (LP) simulations to iteratively refine the PVR of each lung by minimizing the simulated flow and pressure error relative to patients' cardiac magnetic resonance (CMR) and catheterization (CATH) data. While the PVR can also be estimated directly by computing the ratio of pressure gradients and flow from CATH and CMR data, the computational approach can separately identify the different components of PVR along the Glenn pathway, allowing for a more detailed depiction of the Glenn vasculature. Results indicate good correlation between the optimized PVR of the CFD and LP models (n = 16), with an intraclass correlation coefficient (ICC) of 0.998 (p = 0.976) and 0.991 (p = 0.943) for the left and right lung, respectively. Furthermore, compared to CMR flow and CATH pressure data, the optimized PVR estimates result in mean outlet flow and pressure errors of less than 5%. The optimized PVR estimates also agree well with the computed PVR estimates from CATH pressure and CMR flow for both lungs, yielding a mean difference of less than 4%.

Identifiants

pubmed: 39058711
doi: 10.1371/journal.pone.0307890
pii: PONE-D-24-11338
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

e0307890

Informations de copyright

Copyright: © 2024 Laudenschlager et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Déclaration de conflit d'intérêts

The authors have declared that no competing interests exist.

Auteurs

Sebastian Laudenschlager (S)

Department of Radiology, School of Medicine, University of Colorado, Aurora, CO, United States of America.

Samuel Schofield (S)

Department of Cardiology, University of Colorado and Children's Hospital Colorado, Aurora, CO, United States of America.

Nicolas Drysdale (N)

Department of Surgery, School of Medicine, University of Colorado, Aurora, CO, United States of America.

Matthew Stone (M)

Department of Surgery, University of Colorado and Children's Hospital Colorado, Aurora, CO, United States of America.

Jennifer Romanowicz (J)

Department of Cardiology, University of Colorado and Children's Hospital Colorado, Aurora, CO, United States of America.

Benjamin Frank (B)

Department of Cardiology, University of Colorado and Children's Hospital Colorado, Aurora, CO, United States of America.

Michael DiMaria (M)

Department of Cardiology, University of Colorado and Children's Hospital Colorado, Aurora, CO, United States of America.

Vitaly O Kheyfets (VO)

Department of Critical Care, University of Colorado and Children's Hospital Colorado, Aurora, CO, United States of America.

Mehdi Hedjazi-Moghari (M)

Department of Radiology, University of Colorado and Children's Hospital Colorado, Aurora, CO, United States of America.

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