Abstract #2482
Improved Semi-automated Pulse Wave Velocity Analysis in the Thoracic Aorta using 4D flow MRI
Patrick Magrath 1 , Michael Markl 1,2 , Aurelien F. Stalder 3 , Mehmet A. Gulsun 4 , and Bruce Spottiswoode 5
1
Biomedical Engineering, Northwestern
University, Chicago, Illinois, United States,
2
Department
of Radiology, Feinberg School of Medicine, Northwestern
University, Chicago, IL, United States,
3
Siemens
AG Healthcare sector, Erlangen, Germany,
4
Imaging
and Computer Vision, Siemens Corporation, Princeton, New
Jersey, United States,
5
Cardiovascular
MR R&D, Siemens Healthcare, Chicago, Illinois, United
States
Pulse wave velocity (PWV) provides a measure of vessel
stiffness and atherosclerosis. This work presents a
novel, second order surface fitting approach for
estimating pulse wave velocity using a large number of
flow evaluation planes extracted from 4D flow data. This
approach was combined with centerline determination and
lumen segmentation algorithms for a rapid and
semi-automated assessment of PWV, with results that are
more stable to parameter variations than those
calculated using time-to-foot and surface fitting
methods. Further investigation into the use of this and
other complex fitting algorithms is warranted.
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