Image Processing Reference
In-Depth Information
measurements of blood-flow velocity fields. This chapter presents the visualization
challenges for both simulation and real measurements of unsteady blood-flow fields.
25.1 Introduction
Cardiovascular disease (CVD) is a class of conditions affecting the heart and blood
vessels, with an estimated overall prevalence of over thirty percent of the American
population [
1
], and is currently the leading cause of death worldwide [
53
].
Diagnosis of CVD typically involves an evaluation of both the anatomical struc-
ture and function, while the behavior of blood flow is still rarely inspected. The flow
behavior is, nevertheless, of vital importance to the cardiovascular system. Mor-
phology of cardiovascular tissue is significantly influenced by the unsteady behavior
of flowing blood and vice versa. Therefore, blood flow analysis potentially har-
bors a considerable value for both diagnosis and risk assessment. A wide range of
pre-clinical research indicates that flow behavior directly relates to medical condi-
tions [
13
,
28
].
In particular, congenital heart diseases imply anomalous hemodynamics that
strongly influence the progression and treatment of the innate defects. For the adult
case, a noteworthy application is the aortic dissection, which is caused by a tear in
the inner aortic wall. This allows blood to flow between the disintegrated layers of
the vessel wall, resulting in a high risk of rupture. Again, the blood flow behavior
plays a predominant role in the course of the condition. Decision support in case of
cerebral aneurysms is one of the main applications of blood flow analysis. Blood flow
is essential for the assessment of risk of rupture, urgency of treatment in case of mul-
tiple aneurysms, selection of treatment strategy (e.g., coiling/stenting, neurosurgical
clipping).
The analysis of hemodynamic characteristics involves qualitative and quantitative
inspection of the blood flow field. Physicians in clinical research investigate both the
spatiotemporal flow behavior, as well as derived measures, such as the mean flux or
cardiac output. The analysis of the blood flow data often requires complex mental
reconstruction processes by the physician. Visualization plays an important role in
the qualitative exploration, as well as the definition of relevant quantitative measures
and its validation.
There are two main approaches to obtain information about the blood flow: simu-
lations (i.e., computational fluid dynamics) and in-vivo measurements. Both of these
methodologies can obtain information about the unsteady blood flow characteristics,
where each has different advantages and disadvantages.
Although research on simulations of blood flow has been active for several
decades, still a lot of open problems remain concerning accuracy and patient-specific
solutions. Recently, research around measurement of blood flow has increased con-
siderably. Developments inmagnetic resonance imaging (MRI) have made the acqui-
sition of 3D quantitative measurements of blood flow velocities fields possible. Fur-
thermore, several vendors have made essential postprocessing software to inspect
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