Group-wise construction of reduced models for understanding and characterization of pulmonary blood flows from medical images

Abstract

Abstract3D computational fluid dynamics (CFD) in patient-specific geometries provides complementary insights to clinical imaging, to better understand how heart disease, and the side effects of treating heart disease, affect and are affected by hemodynamics. This information can be useful in treatment planning for designing artificial devices that are subject to stress and pressure from blood flow. Yet, these simulations remain relatively costly within a clinical context. The aim of this work is to reduce the complexity of patient-specific simulations by combining image analysis, computational fluid dynamics and model order reduction techniques. The proposed method makes use of a reference geometry estimated as an average of the population, within an efficient statistical framework based on the currents representation of shapes. Snapshots of blood flow simulations performed in the reference geometry are used to build a POD (Proper Orthogonal Decomposition) basis, which can then be mapped on new patients to perform reduced order blood flow simulations with patient specific boundary conditions. This approach is applied to a data-set of 17 tetralogy of Fallot patients to simulate blood flow through the pulmonary artery under normal (healthy or synthetic valves with almost no backflow) and pathological (leaky or absent valve with backflow) conditions to better understand the impact of regurgitated blood on pressure and velocity at the outflow tracts.The model reduction approach is further tested by performing patient simulations under exercise and varying degrees of pathophysiological conditions based on reduction of reference solutions (rest and medium backflow conditions respectively).

Blood Flow Simulations for the Design of Stented Valve Reducer in Enlarged Ventricular Outflow Tracts

“…This is done by solving numerically a hyperelasticity problem on the original three-dimensional geometry (imagined as filled by an elastic material) and applying a surface normal force on the reducer surface. This approach allows to easily obtain a computational domain with a different reducer diameter as a one-to-one deformation of the original configuration, hence without the need of regenerating the three-dimensional mesh (see, e.g., 19 ).…”

“…It could also include other physiological states, such as exercise conditions. 19,32,38 A point of biomedical interest is that introduction of the reducer alone increases pressure loss more than with the full device (PPVR). This is due to the fact that overall the reducer adds a resistance in the system, whereas the full device significantly lowers forward flows while increasing mean flow.…”

“…29 Connected computational blood flow simulations describe the fluid mechanics due to replacement of other types of valves (typically mechanical aortic valves, e.g., 39 ) or on the hemodynamic forces that can explain the direction of stented graft migration in other arteries (e.g., the aorta 26 ). Previous hemodynamics modeling works after ToF repair studied pulmonary regurgitation with 0D 20 or 3D simulations, 12,19 but none of these have been performed yet in the context of this percutaneous pulmonary valve reducer (PPVR).…”

“…36,38 The same approach could be applied for other heart valve functional replacements assessment. 27 In our previous work 19 hemodynamics in patient-specific repaired ToF pulmonary arteries, including some with enlarged outflow tracts, were simulated but without any device. In this study, the impact on hemodynamics of such a PPVR is for the first time investigated.…”

On a sparse pressure-flow rate condensation of rigid circulation models

“…Finally, additional recent work on reduced order modeling with cardiovascular applications can be found in McLeod et al (2010), Guibert et al (2014), Colciago (2014), Ballarin (2015).…”