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Accelerated Estimation of Pulmonary Artery Stenosis Pressure Gradients with Distributed Lumped Parameter Modeling vs. 3D CFD with Instantaneous Adaptive Mesh Refinement: Experimental Validation in Swine

Annals of Biomedical Engineering volume 49, pages 2365–2376 (2021)Cite this article

Abstract

Branch pulmonary artery stenosis (PAS) commonly occurs in congenital heart disease and the pressure gradient over a stenotic PA lesion is an important marker for re-intervention. Image based computational fluid dynamics (CFD) has shown promise for non-invasively estimating pressure gradients but one limitation of CFD is long simulation times. The goal of this study was to compare accelerated predictions of PAS pressure gradients from 3D CFD with instantaneous adaptive mesh refinement (AMR) versus a recently developed 0D distributed lumped parameter CFD model. Predictions were then experimentally validated using a swine PAS model (n = 13). 3D CFD simulations with AMR improved efficiency by 5 times compared to fixed grid CFD simulations. 0D simulations further improved efficiency by 6 times compared to the 3D simulations with AMR. Both 0D and 3D simulations underestimated the pressure gradients measured by catheterization (− 1.87 ± 4.20 and − 1.78 ± 3.70 mmHg respectively). This was partially due to simulations neglecting the effects of a catheter in the stenosis. There was good agreement between 0D and 3D simulations (ICC 0.88 [0.66–0.96]) but only moderate agreement between simulations and experimental measurements (0D ICC 0.60 [0.11–0.86] and 3D ICC 0.66 [0.21–0.88]). Uncertainty assessment indicates that this was likely due to limited medical imaging resolution causing uncertainty in the segmented stenosis diameter in addition to uncertainty in the outlet resistances. This study showed that 0D lumped parameter models and 3D CFD with instantaneous AMR both improve the efficiency of hemodynamic modeling, but uncertainty from medical imaging resolution will limit the accuracy of pressure gradient estimations.

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Acknowledgments

This investigation was supported by the Clinical and Translational Science Award (CTSA) program, through the NIH National Center for Advancing Translational Sciences (NCATS), Grant UL1TR002373 (AR and LL) and under the NIH Ruth L. Kirschstein National Research Service Award T32 HL 007936 from the National Heart Lung and Blood Institute to the University of Wisconsin-Madison Cardiovascular Research Center (RP). The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH. This investigation used the compute resources and assistance of the UW-Madison Center For High Throughput Computing (CHTC) in the Department of Computer Sciences. The CHTC is supported by UW-Madison, the Advanced Computing Initiative, the Wisconsin Alumni Research Foundation, the Wisconsin Institutes for Discovery, and the National Science Foundation, and is an active member of the Open Science Grid, which is supported by the National Science Foundation and the U.S. Department of Energy’s Office of Science.

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Affiliations

  1. Biomedical Engineering, University of Wisconsin, Madison, WI, USA

    Ryan Pewowaruk & Alejandro Roldán-Alzate

  2. Pediatrics, Division of Cardiology, University of Wisconsin, Madison, WI, USA

    Luke Lamers

  3. Mechanical Engineering, University of Wisconsin, Madison, WI, USA

    Alejandro Roldán-Alzate

  4. Radiology, University of Wisconsin, Madison, WI, USA

    Alejandro Roldán-Alzate

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  1. Ryan Pewowaruk
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Correspondence to Alejandro Roldán-Alzate.

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Pewowaruk, R., Lamers, L. & Roldán-Alzate, A. Accelerated Estimation of Pulmonary Artery Stenosis Pressure Gradients with Distributed Lumped Parameter Modeling vs. 3D CFD with Instantaneous Adaptive Mesh Refinement: Experimental Validation in Swine. Ann Biomed Eng 49, 2365–2376 (2021). https://doi.org/10.1007/s10439-021-02780-5

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Keywords

  • Congenital heart disease
  • Branch pulmonary artery stenosis
  • Non-invasive diagnostics