Renske Merton, Daan Bosshardt, Gustav J Strijkers, Aart J Nederveen, Eric M Schrauben, Pim van Ooij
{"title":"利用自动三维动态平衡 SSFP MRI 分段评估主动脉运动。","authors":"Renske Merton, Daan Bosshardt, Gustav J Strijkers, Aart J Nederveen, Eric M Schrauben, Pim van Ooij","doi":"10.1016/j.jocmr.2024.101089","DOIUrl":null,"url":null,"abstract":"<p><strong>Purpose: </strong>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.</p><p><strong>Methods: </strong>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.</p><p><strong>Results: </strong>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.</p><p><strong>Conclusion: </strong>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.</p>","PeriodicalId":15221,"journal":{"name":"Journal of Cardiovascular Magnetic Resonance","volume":null,"pages":null},"PeriodicalIF":4.2000,"publicationDate":"2024-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Assessing Aortic Motion with Automated 3D Cine Balanced SSFP MRI Segmentation.\",\"authors\":\"Renske Merton, Daan Bosshardt, Gustav J Strijkers, Aart J Nederveen, Eric M Schrauben, Pim van Ooij\",\"doi\":\"10.1016/j.jocmr.2024.101089\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Purpose: </strong>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.</p><p><strong>Methods: </strong>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.</p><p><strong>Results: </strong>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.</p><p><strong>Conclusion: </strong>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.</p>\",\"PeriodicalId\":15221,\"journal\":{\"name\":\"Journal of Cardiovascular Magnetic Resonance\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":4.2000,\"publicationDate\":\"2024-08-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Cardiovascular Magnetic Resonance\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1016/j.jocmr.2024.101089\",\"RegionNum\":1,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"CARDIAC & CARDIOVASCULAR SYSTEMS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Cardiovascular Magnetic Resonance","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1016/j.jocmr.2024.101089","RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"CARDIAC & CARDIOVASCULAR SYSTEMS","Score":null,"Total":0}
Assessing Aortic Motion with Automated 3D Cine Balanced SSFP MRI Segmentation.
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.
期刊介绍:
Journal of Cardiovascular Magnetic Resonance (JCMR) publishes high-quality articles on all aspects of basic, translational and clinical research on the design, development, manufacture, and evaluation of cardiovascular magnetic resonance (CMR) methods applied to the cardiovascular system. Topical areas include, but are not limited to:
New applications of magnetic resonance to improve the diagnostic strategies, risk stratification, characterization and management of diseases affecting the cardiovascular system.
New methods to enhance or accelerate image acquisition and data analysis.
Results of multicenter, or larger single-center studies that provide insight into the utility of CMR.
Basic biological perceptions derived by CMR methods.