Abstract
Background: Pre-clinical detection of atherosclerosis enables personalized preventive strategies in asymptomatic individuals. Cardiovascular magnetic resonance (CMR) has evolved as an attractive imaging modality for studying atherosclerosis in vivo. Yet, the majority of aortic CMR studies and proposed sequences to date have been performed at 1.5 tesla using 2D BB techniques and a slice thickness of 4-5 mm. Here, we evaluate for the first time the reproducibility of an isotropic, T1-weighted, three-dimensional, black-blood, CMR VISTA sequence (3D-T1-BB-VISTA) for quantification of aortic wall characteristics in healthy, young adults. Methods: In 20 healthy, young adults (10 males, mean age 31.3 years) of the AMBITYON cohort study the descending thoracic aorta was imaged with a 3.0 T MR system using the 3D-T1-BB-VISTA sequence. The inter-scan, inter-rater and intra-rater reproducibility of aortic lumen, total vessel and wall area and mean and maximum wall thickness was evaluated using Bland-Altman analyses and Intraclass Correlation Coefficients (ICC). Based on these findings, sample sizes for detecting differences in aortic wall characteristics between groups were calculated. Results: For each studied parameter, the inter-scan, inter-rater and intra-rater reproducibility was excellent as indicated by narrow limits of agreement and high ICCs (ranging from 0.76 to 0.99). Sample sizes required to detect a 5 % difference in aortic wall characteristics between two groups were 203, 126, 136, 68 and 153 per group for lumen area, total vessel area and vessel wall area and for mean and maximum vessel wall thickness, respectively. Conclusion: The 3D-T1-BB-VISTA sequence provides excellent reproducibility for quantification of aortic wall characteristics and can detect small differences between groups with reasonable sample sizes. Hence, it may be a valuable tool for assessment of the subtle vascular wall changes of early atherosclerosis in asymptomatic populations.
Dokumententyp: | Zeitschriftenartikel |
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Fakultät: | Medizin |
Themengebiete: | 600 Technik, Medizin, angewandte Wissenschaften > 610 Medizin und Gesundheit |
URN: | urn:nbn:de:bvb:19-epub-37924-8 |
ISSN: | 1097-6647 |
Sprache: | Englisch |
Dokumenten ID: | 37924 |
Datum der Veröffentlichung auf Open Access LMU: | 04. Mai 2017, 13:10 |
Letzte Änderungen: | 04. Nov. 2020, 14:44 |