Publication# The non-circular shape of FloWatch®-PAB prevents the need for pulmonary artery reconstruction after banding

Alfio Quarteroni, Ludwig Von Segesser, Paolo Zunino

*Elsevier Science B.V., Oxford, *2006

Journal paper

Journal paper

Abstract

To evaluate the differences between non-circular shape of FloWatch®-PAB and conventional pulmonary artery (PA) banding. Methods: Geometrical analysis. Conventional banding and FloWatch®-PAB perimeters were plotted against cross-sections. Computational fluid dynamics (CFD) model. CFD compared non-circular FloWatch®-PAB cross-sections with conventional banding regarding pressure gradients. Clinical data. Seven children, median age 2 months (7 days to 3 years), median weight 4.2 kg (3.2–9.8 kg), with complex congenital heart defects underwent PA banding with FloWatch®-PAB implantation. Results: Geometrical analysis. Conventional banding: progressive reduction of cross-sections was accompanied by progressive reduction of PA perimeters. FloWatch®-PAB: with equal reduction of cross-sections the PA perimeter remained constant. CFD model. Non-circular and circular banding provided same trans-banding pressure gradients for same cross-sections at any given flow. Clinical data. Mean PA internal diameter at banding was 13.3 ± 4.5 mm. After a mean interval of 5.9 ± 3.7 months, all children underwent intra-cardiac repair and simple FloWatch®-PAB removal without PA reconstruction. Mean PA internal diameter with FloWatch®-PAB removal increased from 3.0 ± 0.8 to 12.4 ± 4.5 mm (normal mean internal diameter for the age = 9.9 ± 1.6). No residual pressure gradient was recorded in correspondence of the site of the previous FloWatch®-PAB implantation in 6/7 patients, 10 mmHg peak and 5 mmHg mean gradient in 1/7. Conclusions: The non-circular shape of FloWatch®-PAB can replace conventional circular banding with the following advantages: (a) the pressure gradient will remain essentially the same as for conventional circular banding for any given cross-section, but with significantly smaller reduction of PA perimeter; and (b) PA reconstruction at the time of de-banding for intra-cardiac repair can be avoided.

Official source

This page is automatically generated and may contain information that is not correct, complete, up-to-date, or relevant to your search query. The same applies to every other page on this website. Please make sure to verify the information with EPFL's official sources.

Related concepts

Loading

Related publications

Loading

Related publications (2)

Loading

Loading

Related concepts (11)

Gradient

In vector calculus, the gradient of a scalar-valued differentiable function f of several variables is the vector field (or vector-valued function) \nabla f whose value at a

Computational fluid dynamics

Computational fluid dynamics (CFD) is a branch of fluid mechanics that uses numerical analysis and data structures to analyze and solve problems that involve fluid flows. Computers are used to perfor

Geometric analysis

Geometric analysis is a mathematical discipline where tools from differential equations, especially elliptic partial differential equations (PDEs), are used to establish new results in differential

Claudia Maria Colciago, Simone Deparis, Davide Forti

Several models exist for the simulation of vascular flows; they span from simple circuit models to full three-dimensional ones that take into account detailed features of the blood and of the arterialwall. Eachmodel comeswith both benefits and drawbacks, the main denominator being a compromise between detailed resolution requirements versus computational time. We first present a fluid-structure interaction computationalmodelwhere both the fluid and the structure are three dimensional. In particular, the fluid includes modeling of large eddies by the variationalmultiscalemethod. After time and space discretizations carried out by finite differences and finite elements, respectively, we set up a parallel solver based ondomain decomposition and a FaCSI preconditioner. These simulations allow one to capture details of the flow dynamics and of the structure deformation even in the transitional regime characterizing hemodynamics in the aorta. It takes roughly 10 hours to complete a simulation of one heartbeat with 35 million degrees of freedom on 2048 cores. We then reduce both the model and its numerical complexity. The structural model is simplified to a two-dimensional membrane located at the fluid-structure interface and the fluid computational domain is fixed. For a fixed geometry andmesh, these assumptions allow one to apply proper orthogonal decomposition and generate a space discretization which has only a few dozen degrees of freedom. It is then possible to perform the simulation of one heartbeat on a laptop in less than one second. Themodeling and numerical reduction therefore allows a dramatic reduction of computational time. However, the price to pay comes, on the one hand, in terms of the preparation of a reduced basis specific to the patient and the geometry of the vessel and, on the other hand, with a detriment of certain quantities of interest. For example, when using a finite element discretization with 9 million degrees of freedom, the offline part takes about 12 hours on 720 cores for the example provided in this work; in this case, the flow profiles in the aorta are pretty close to the full three-dimensional

Alfio Quarteroni, Christian Vergara

This review paper addresses the so called geometric multiscale approach for the numerical simulation of blood flow problems, from its origin (that we can collocate in the second half of ’90s) to our days. By this approach the blood fluid-dynamics in the whole circulatory system is described mathematically by means of heterogeneous problems featuring different degree of detail and different geometric dimension that interact together through appropriate interface coupling conditions. Our review starts with the introduction of the stand-alone problems, namely the 3D fluidstructure interaction problem, its reduced representation by means of 1D models, and the so-called lumped parameters (aka 0D) models, where only the dependence on time survives. We then address specific methods for stand-alone 3D models when the available boundary data are not enough to ensure the mathematical well posedness. These so-called “defective problems” naturally arise in practical applications of clinical relevance but also because of the interface coupling of heterogeneous problems that are generated by the geometric multiscale process. We also describe specific issues related to the boundary treatment of reduced models, particularly relevant to the geometric multiscale coupling. Next, we detail the most popular numerical algorithms for the solution of the coupled problems. Finally, we review some of the most representative works - from different research groups - which addressed the geometric multiscale approach in the past years. A proper treatment of the different scales relevant to the hemodynamics and their interplay is essential for the accuracy of numerical simulations and eventually for their clinical impact. This paper aims at providing a state-of-the-art picture of these topics, where the gap between theory and practice demands rigorous mathematical models to be reliably filled.