Scan-rescan reproducibility of segmental aortic wall shear stress as assessed by phase-specific segmentation with 4D flow MRI in healthy volunteers

利用4D流磁共振成像进行相位特异性分割,评估健康志愿者主动脉壁节段剪切应力的扫描-重扫描重复性

阅读:1

Abstract

OBJECTIVE: The aim was to investigate scan-rescan reproducibility and observer variability of segmental aortic 3D systolic wall shear stress (WSS) by phase-specific segmentation with 4D flow MRI in healthy volunteers. MATERIALS AND METHODS: Ten healthy volunteers (age 26.5 ± 2.6 years) underwent aortic 4D flow MRI twice. Maximum 3D systolic WSS (WSSmax) and mean 3D systolic WSS (WSSmean) for five thoracic aortic segments over five systolic cardiac phases by phase-specific segmentations were calculated. Scan-rescan analysis and observer reproducibility analysis were performed. RESULTS: Scan-rescan data showed overall good reproducibility for WSSmean (coefficient of variation, COV 10-15%) with moderate-to-strong intraclass correlation coefficient (ICC 0.63-0.89). The variability in WSSmax was high (COV 16-31%) with moderate-to-good ICC (0.55-0.79) for different aortic segments. Intra- and interobserver reproducibility was good-to-excellent for regional aortic WSSmax (ICC ≥ 0.78; COV ≤ 17%) and strong-to-excellent for WSSmean (ICC ≥ 0.86; COV ≤ 11%). In general, ascending aortic segments showed more WSSmax/WSSmean variability compared to aortic arch or descending aortic segments for scan-rescan, intraobserver and interobserver comparison. CONCLUSIONS: Scan-rescan reproducibility was good for WSSmean and moderate for WSSmax for all thoracic aortic segments over multiple systolic phases in healthy volunteers. Intra/interobserver reproducibility for segmental WSS assessment was good-to-excellent. Variability of WSSmax is higher and should be taken into account in case of individual follow-up or in comparative rest-stress studies to avoid misinterpretation.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。