Assessing Aortic Motion with Automated 3D Cine Balanced SSFP MRI Segmentation.

Abstract

Purpose: To apply free-running three-dimensional (3D) cine balanced steady state free precession (bSSFP) CMR framework in combination with 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 about 4minutes facilitated by pseudo-spiral Cartesian undersampling and compressed-sensing reconstruction. Automated segmentation of 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 motion, as well as the measurement and change in diameter of the ascending aorta.

Results: A total of 14 adult healthy volunteers (median age, 28 years (IQR: 26.0-31.3), 6 female) were included. Automated segmentation compared to manual segmentation of the aorta test set showed a Dice score of 0.93 ± 0.02. The median (interquartile range) over all volunteers for the largest maximum and mean ascending aorta (AAo) displacement in the first scan was 13.0 (4.4) mm and 5.6 (2.4) mm, respectively. Peak mean diameter in the AAo was 25.9 (2.2) mm and peak mean diameter change was 1.4 (0.5) mm. The maximum individual variability over the three repeated scans of maximum and mean AAo displacement was 3.9 (1.6) mm and 2.2 (0.8) mm, respectively. The maximum individual variability of mean diameter and diameter change were 1.2 (0.5) mm and 0.9 (0.4) mm.

Conclusion: A free-running 3D cine bSSFP CMR scan with a scan time of four minutes combined with an automated nnU-net segmentation consistently captured the aorta's cardiac motion-related 4D displacement, diameter, and diameter change.