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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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