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Design and execution of a verification, validation, and uncertainty quantification plan for a numerical model of left ventricular flow after LVAD implantation.

Authors :
Santiago A
Butakoff C
Eguzkitza B
Gray RA
May-Newman K
Pathmanathan P
Vu V
Vázquez M
Source :
PLoS computational biology [PLoS Comput Biol] 2022 Jun 13; Vol. 18 (6), pp. e1010141. Date of Electronic Publication: 2022 Jun 13 (Print Publication: 2022).
Publication Year :
2022

Abstract

Background: Left ventricular assist devices (LVADs) are implantable pumps that act as a life support therapy for patients with severe heart failure. Despite improving the survival rate, LVAD therapy can carry major complications. Particularly, the flow distortion introduced by the LVAD in the left ventricle (LV) may induce thrombus formation. While previous works have used numerical models to study the impact of multiple variables in the intra-LV stagnation regions, a comprehensive validation analysis has never been executed. The main goal of this work is to present a model of the LV-LVAD system and to design and follow a verification, validation and uncertainty quantification (VVUQ) plan based on the ASME V&V40 and V&V20 standards to ensure credible predictions.<br />Methods: The experiment used to validate the simulation is the SDSU cardiac simulator, a bench mock-up of the cardiovascular system that allows mimicking multiple operation conditions for the heart-LVAD system. The numerical model is based on Alya, the BSC's in-house platform for numerical modelling. Alya solves the Navier-Stokes equation with an Arbitrary Lagrangian-Eulerian (ALE) formulation in a deformable ventricle and includes pressure-driven valves, a 0D Windkessel model for the arterial output and a LVAD boundary condition modeled through a dynamic pressure-flow performance curve. The designed VVUQ plan involves: (a) a risk analysis and the associated credibility goals; (b) a verification stage to ensure correctness in the numerical solution procedure; (c) a sensitivity analysis to quantify the impact of the inputs on the four quantities of interest (QoIs) (average aortic root flow [Formula: see text], maximum aortic root flow [Formula: see text], average LVAD flow [Formula: see text], and maximum LVAD flow [Formula: see text]); (d) an uncertainty quantification using six validation experiments that include extreme operating conditions.<br />Results: Numerical code verification tests ensured correctness of the solution procedure and numerical calculation verification showed a grid convergence index (GCI)95% <3.3%. The total Sobol indices obtained during the sensitivity analysis demonstrated that the ejection fraction, the heart rate, and the pump performance curve coefficients are the most impactful inputs for the analysed QoIs. The Minkowski norm is used as validation metric for the uncertainty quantification. It shows that the midpoint cases have more accurate results when compared to the extreme cases. The total computational cost of the simulations was above 100 [core-years] executed in around three weeks time span in Marenostrum IV supercomputer.<br />Conclusions: This work details a novel numerical model for the LV-LVAD system, that is supported by the design and execution of a VVUQ plan created following recognised international standards. We present a methodology demonstrating that stringent VVUQ according to ASME standards is feasible but computationally expensive.<br />Competing Interests: I have read the journal’s policy and the authors of this manuscript have the following competing interests: AS, MV, BE and CB have acted as consultants for Medtronic PLC related to Medtronic’s HVAD. KMN and VV have an ongoing research study for Abbott, Inc for work on Abbott’s HeartMate III. RG and PP need to include the following statement: “The mention of commercial products, their sources, or their use in connection with material reported herein is not to be construed as either an actual or implied endorsement of such products by the U.S. Department of Health and Human Services”.

Details

Language :
English
ISSN :
1553-7358
Volume :
18
Issue :
6
Database :
MEDLINE
Journal :
PLoS computational biology
Publication Type :
Academic Journal
Accession number :
35696442
Full Text :
https://doi.org/10.1371/journal.pcbi.1010141