Simulations of congenital septal defect closure and reactivity testing in patient-specific models of the pediatric pulmonary vasculature: A 3D numerical study with fluid-structure interaction

Abstract

Clinical imaging methods are highly effective in the diagnosis of vascular pathologies, but they do not currently provide enough detail to shed light on the cause or progression of such diseases, and would be hard pressed to foresee the outcome of surgical interventions. Greater detail of and prediction capabilities for vascular hemodynamics and arterial mechanics are obtained here through the coupling of clinical imaging methods with computational techniques. Three-dimensional, patient-specific geometric reconstructions of the pediatric proximal pulmonary vasculature were obtained from x-ray angiogram images and meshed for use with commercial computational software. Two such models from hypertensive patients, one with multiple septal defects, the other who underwent vascular reactivity testing, were each completed with two sets of suitable fluid and structural initial and boundary conditions and used to obtain detailed transient simulations of artery wall motion and hemodynamics in both clinically measured and predicted configurations. The simulation of septal defect closure, in which input flow and proximal vascular stiffness were decreased, exhibited substantial decreases in proximal velocity, wall shear stress (WSS), and pressure in the post-op state. The simulation of vascular reactivity, in which distal vascular resistance and proximal vascular stiffness were decreased, displayed negligible changes in velocity and WSS but a significant drop in proximal pressure in the reactive state. This new patient-specific technique provides much greater detail regarding the function of the pulmonary circuit than can be obtained with current medical imaging methods alone, and holds promise for enabling surgical planning.

Fig. 1

Steps in the production of patient-specific computational meshes: (a) Example AP (a) and lateral (b) pulmonary bi-plane angiogram images with centerline data overlaid on the AP view and centerline and diameter overlaid on the lateral view. The skeleton data viewed in the solid modeling environment (c) and resulting surfaces (d) note that the MPA and LPA are represented by one surface (B1) and the RPA by another surface (B2). (e) The complete base line mesh; fluid domains are shown in red (normal) and blue (porous), and structure domains are shown in green (normal compliance) and yellow (stiff). (f) A typical cross section of the base line mesh.

Fig. 2

Anterior (Ax) and inferior (Ix) views of four computational meshes derived from patient-specific geometry (exit sections not shown). Light and dark gray surfaces denote the structural domain and fluid inlet, respectively. Thick black lines denote cross-sectional cut locations at which secondary flows and wall shear stress are examined in the results section.

Fig. 3

Oblique superior view of velocity vectors and velocity magnitude contours within a transverse mid-vessel slice of the MPA and proximal PA branches of model 1 at eight time points within the cardiac cycle. The thick gray circle at the top of the figure is the MPA inlet slice; thin gray lines outline the artery shape distal to the inlet. The change in domain shape is due to arterial wall motion, and the velocity contour color mapping is consistent through the series.

Fig. 4

Primary velocity fields, pressures, and WSS from model 1 under pre-op and post-op conditions

Fig. 5

Primary velocity fields, pressures, and WSS at a cross section of the RPA from model 2 under hypertensive and reactive conditions