Keywords: Vascular, Blood vessels, Marfan
Motivation: New biomarkers are needed to guide aortic surgery to prevent aortic dissection in Marfan syndrome (MFS).
Goal(s): To investigate differences in aortic motion between healthy volunteers and (subgroups of) MFS patients.
Approach: We apply a recently published novel non-contrast enhanced, free breathing, time-resolved 3D balanced steady free precession CMR scan with a machine learning based algorithm for automatic aortic segmentations to evaluate 4D aortic motion.
Results: We found significant differences in aortic motion between patients with- and without a history of aortic root surgery and healthy volunteers. Thus, aortic motion might be a novel marker for aortic disease severity in MFS.
Impact: The differences in 4D aortic motion measured using 3D CINE balanced steady state free precession CMR between healthy volunteers and (subgroups of) Marfan syndrome patients might provide a new marker for disease severity in Marfan syndrome.
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