Assessing aortic motion with automated 3D cine balanced steady state free precession cardiovascular magnetic resonance segmentation.

ABSTRACT:

Purpose

To apply a free-running three-dimensional (3D) cine balanced steady state free precession (bSSFP) cardiovascular magnetic resonance (CMR) framework in combination with artificial intelligence (AI) segmentations to quantify time-resolved aortic displacement, diameter and diameter change.

Methods

In this prospective study, we implemented a free-running 3D cine bSSFP sequence with scan time of approximately 4 min facilitated by pseudo-spiral Cartesian undersampling and compressed-sensing reconstruction. Automated segmentation of the aorta in all cardiac timeframes was applied through the use of nnU-Net. Dynamic 3D motion maps were created for three repeated scans per volunteer, leading to the detailed quantification of aortic motion, as well as the measurement and chang

SUBMITTER: Merton R 

PROVIDER: S-EPMC11615597 | biostudies-literature | 2024 Winter

REPOSITORIES: biostudies-literature