Meeting Banner
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.

This abstract and the presentation materials are available to members only; a login is required.

Join Here