Abstract #0247
Hemodynamic Fingerprinting of Altered 3D Blood Characteristics in Aortic Disease
Julio Garcia 1 , Alex J. Barker 1 , Pim van Ooij 1 , Susanne Schnell 1 , S. Chris Malaisrie 2 , Jeremy Collins 1 , James Carr 1 , and Michael Markl 1
1
Radiology, Northwestern University, Chicago,
Illinois, United States,
2
Division
of Cardiac Surgery, Northwestern University, Chicago,
Illinois, United States
Time-resolved 3D PC-MRI data analysis can be time
consuming and often relies on the manual placement of 2D
analysis planes at user defined vascular regions of
interest. The inherent volumetric 3D coverage of the
vascular system of interest provided by 4D flow MRI is
not fully utilized by analysis based on 2D planes. It
was thus the aim of this study to evaluate a novel
automated flow distribution analysis based on the
evaluation the blood flow velocity distributions in the
entire 3D vessel segments to identify hemodynamic
'fingerprints' of different aortic pathologies.
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