Biomedical Engineering Reference
In-Depth Information
associated predicted hemodynamic parameters. The role of CFD, coupled with
patient-specific inflow conditions, for treatment decisions of aortic pathologies
was presented in [
10
]. In [
11
], hemodynamics simulations are investigated in the
context of coronary artery disease management. The major limitation of previously
published methods is the lack of scalability. Approaches are customized for a
limited number of well-chosen patients (usually 1-3) and involve a cascade of
tedious manual processing tasks, which result in hardly reproducible results.
We propose a unified computational framework for large-scale hemodynamic
modeling and simulations in pediatric cardiology to aid diagnostic and therapy
decision making in patients affected by congenital disease of the AV and the aorta.
Our method provides a deterministic and streamlined processing pipeline to per-
form CFD simulations from patient-specific data. The proposed method includes an
automated approach to segment the centerline and lumen of the aorta as well as the
inlet and outlet flow profiles over the entire cardiac cycle. CFD simulations are
performed using an embedded boundary method solved within a level-set formula-
tion. We demonstrate the capabilities of our framework by performing blood flow
simulations on selected patients coming from an FDA-sponsored multicenter clini-
cal trial, Coarctation Of the Aorta Stent Trial (COAST). To this end, we present
flow pattern analysis in three patients that suffer from aortic coarctation and various
types of AV dysfunctions.
2 Description of Method
Within this section, we describe in detail each component of the proposed simula-
tion framework as is illustrated in Fig.
1
. The integrated steps are: (1) selection and
reconstruction of MR measurements of anatomy and flow (Sect.
2.1
), (2) estimation
Fig. 1 Pipeline of the simulation: (a) volume rendering of a clear, high contrast CE-MRA image
displayed together with a PC-MRI slice used for depicting an aortic arch. (b) Extracted centerline
and segmentation of the aorta. (c) Patient-specific systolic in- and outflow rates derived from PC-
MRI measurement. (d) Simulated blood flow velocities and vorticity magnitude
