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

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. Met...

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Main Authors: Renske Merton, Daan Bosshardt, Gustav J. Strijkers, Aart J. Nederveen, Eric M. Schrauben, Pim van Ooij
Format: Article
Language:English
Published: Elsevier 2024-01-01
Series:Journal of Cardiovascular Magnetic Resonance
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Online Access:http://www.sciencedirect.com/science/article/pii/S1097664724011165
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author Renske Merton
Daan Bosshardt
Gustav J. Strijkers
Aart J. Nederveen
Eric M. Schrauben
Pim van Ooij
author_facet Renske Merton
Daan Bosshardt
Gustav J. Strijkers
Aart J. Nederveen
Eric M. Schrauben
Pim van Ooij
author_sort Renske Merton
collection DOAJ
description 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 change in diameter of the ascending aorta. Results: A total of 14 adult healthy volunteers (median age, 28 years (interquartile range [IQR]: 26.0–31.3), 6 females) were included. Automated segmentation compared to manual segmentation of the aorta test set showed a Dice score of 0.93 ± 0.02. The median (IQR) 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.
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series Journal of Cardiovascular Magnetic Resonance
spelling doaj-art-2e9d97c4ccca4898854ae1fd77121d122025-08-20T01:56:48ZengElsevierJournal of Cardiovascular Magnetic Resonance1097-66472024-01-0126210108910.1016/j.jocmr.2024.101089Assessing aortic motion with automated 3D cine balanced steady state free precession cardiovascular magnetic resonance segmentationRenske Merton0Daan Bosshardt1Gustav J. Strijkers2Aart J. Nederveen3Eric M. Schrauben4Pim van Ooij5Amsterdam UMC location University of Amsterdam, Radiology and Nuclear Medicine, Meibergdreef 9, Amsterdam, the Netherlands; Amsterdam Cardiovascular Sciences, Atherosclerosis and Ischemic Syndromes, Amsterdam, the Netherlands; Corresponding author. Amsterdam UMC location University of Amsterdam, Radiology and Nuclear Medicine, Meibergdreef 9, Amsterdam, the Netherlands.Amsterdam UMC location University of Amsterdam, Radiology and Nuclear Medicine, Meibergdreef 9, Amsterdam, the Netherlands; Amsterdam Cardiovascular Sciences, Atherosclerosis and Ischemic Syndromes, Amsterdam, the NetherlandsAmsterdam UMC location University of Amsterdam, Biomedical Engineering and Physics, Meibergdreef 9, Amsterdam, the NetherlandsAmsterdam UMC location University of Amsterdam, Radiology and Nuclear Medicine, Meibergdreef 9, Amsterdam, the NetherlandsAmsterdam UMC location University of Amsterdam, Radiology and Nuclear Medicine, Meibergdreef 9, Amsterdam, the NetherlandsAmsterdam UMC location University of Amsterdam, Radiology and Nuclear Medicine, Meibergdreef 9, Amsterdam, the Netherlands; Amsterdam Cardiovascular Sciences, Atherosclerosis and Ischemic Syndromes, Amsterdam, the Netherlands; Corresponding author. Amsterdam Cardiovascular Sciences, Atherosclerosis and Ischemic Syndromes, Amsterdam, the Netherlands.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 change in diameter of the ascending aorta. Results: A total of 14 adult healthy volunteers (median age, 28 years (interquartile range [IQR]: 26.0–31.3), 6 females) were included. Automated segmentation compared to manual segmentation of the aorta test set showed a Dice score of 0.93 ± 0.02. The median (IQR) 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.http://www.sciencedirect.com/science/article/pii/S1097664724011165Aortic motion3D displacement3D cine bSSFPAutomated aortic segmentations
spellingShingle Renske Merton
Daan Bosshardt
Gustav J. Strijkers
Aart J. Nederveen
Eric M. Schrauben
Pim van Ooij
Assessing aortic motion with automated 3D cine balanced steady state free precession cardiovascular magnetic resonance segmentation
Journal of Cardiovascular Magnetic Resonance
Aortic motion
3D displacement
3D cine bSSFP
Automated aortic segmentations
title Assessing aortic motion with automated 3D cine balanced steady state free precession cardiovascular magnetic resonance segmentation
title_full Assessing aortic motion with automated 3D cine balanced steady state free precession cardiovascular magnetic resonance segmentation
title_fullStr Assessing aortic motion with automated 3D cine balanced steady state free precession cardiovascular magnetic resonance segmentation
title_full_unstemmed Assessing aortic motion with automated 3D cine balanced steady state free precession cardiovascular magnetic resonance segmentation
title_short Assessing aortic motion with automated 3D cine balanced steady state free precession cardiovascular magnetic resonance segmentation
title_sort assessing aortic motion with automated 3d cine balanced steady state free precession cardiovascular magnetic resonance segmentation
topic Aortic motion
3D displacement
3D cine bSSFP
Automated aortic segmentations
url http://www.sciencedirect.com/science/article/pii/S1097664724011165
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