TY - JOUR T1 - Design and execution of a Verification, Validation, and Uncertainty Quantification plan for a numerical model of left ventricular flow after LVAD implantation JF - bioRxiv DO - 10.1101/2021.11.11.468169 SP - 2021.11.11.468169 AU - Alfonso Santiago AU - Constantine Butakoff AU - Beatriz Eguzkitza AU - Richard A. Gray AU - Karen May-Newman AU - Pras Pathmanathan AU - Vi Vu AU - Mariano Vázquez Y1 - 2021/01/01 UR - http://biorxiv.org/content/early/2021/11/13/2021.11.11.468169.abstract N2 - 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.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 Arbitrarian 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 , maximum aortic root flow , average LVAD flow , and maximum LVAD flow ); (d) an uncertainty quantification using six validation experiments that include extreme operating conditions.Results Numerical code verification tests ensured correctness of the solution procedure and numerical calculation verification showed small numerical errors. 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.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.Competing Interest StatementAS, MV, BE and CB have acted as consultants for Medtronic PLC related with Medtronic's HVAD. KMN and VV have an ongoing research study for Abbott, Inc for work on Abbott's HeartMate IIINomenclatureALEArbitrarian Lagrangian-Eulerian. 1,5AoVAortic Valve. 2, 19ASGSalgebraic subgrid scale. 5ASMEAmerican Society of Mechanical Engineers. 3 7, 15, 16, 21BSAbody surface area. 2, 19BSCBarcelona Supercomputing Center. 5CDFcumulative distribution function. 9CFDcomputational fluid dynamics. 3, 5, 9-11, 13, 15CoUcontext of use. 6-8, 17, 18CScardiac simulator. 3, 9, 11, 21DAREDakota server. 5, 6ECDFempirical cumulative distribution function. 9, 11 12,14-16, 18-20EDVend diastolic volume. 3-5EFEjection Fraction. 4, 6, 10, 11, 19-21ESVend systolic volume. 4, 5FDAFood and Drug Administration. 3FEMfinite elements method. 5FSIfluid-structure interaction. 3-5GMRESgeneralized minimal residual method. 5HFheart failure. 2, 4, 6HPChigh performance computing. 6HRheart rate. 2, 6, 10-12, 19-21KDEkernel distribution estimation. 12, 14LHSlatin hypercube sampling. 9, 10, 12LVleft ventricle. 1-7, 9, 10, 18, 19, 21LVADleft ventricular assist device. 1-7, 9-12, 14-16, 18-22MNMinkowskiLļ norm. 9, 11-13NCVnumerical code verification. 7, 16NYHANew York heart association. 4PCEpolynomial chaos expansion. 9PRACEPartnership for Advanced Computing in Europe. 16QoIquantity of interest. 1, 6-15, 17-19, 21RVright ventricle. 2, 19SAsensitivity analysis. 5-11, 13, 16, 17, 21, 22SDSUSan Diego State University. 3, 9, 11, 21, 22SQAsoftware quality assurance. 7, 8, 16UEABSUnified European Applications Benchmark Suite. 16UQuncertainty quantification. 4-13, 15-17, 21, 22VVUQverification, validation and uncertainty quantification. 1,3, 6, 7, 9, 17, 21 ER -