UTE-T2∗ mapping of human articular cartilage in vivo: a repeatability assessment

UTE-T2∗成像技术在人体关节软骨体内的应用:重复性评估

阅读:4

Abstract

INTRODUCTION: Ultrashort echo-time enhanced T2∗ (UTE-T2∗) mapping of articular cartilage is a novel quantitative MRI technique with the potential to visualize deep cartilage characteristics better than standard T2 mapping. The feasibility and intersession repeatability of UTE-T2∗ mapping of cartilage in vivo has not previously been evaluated. METHODS: Eleven asymptomatic subjects underwent repeat UTE-T2∗ imaging on a whole-body 3T MRI scanner on three consecutive days. Full-thickness, superficial and deep regions of interest (ROIs) were evaluated in the central weight-bearing zones of the medial femoral condyle (cMFC) and tibial plateau (cMTP). Intersession precision error across subjects was evaluated by the root-mean-square average coefficients of variation (RMSA-CV) and by the median of intra-subject standard deviations (SDs) of UTE-T2∗ values in each ROI. RESULTS: UTE-T2∗ values in vivo were found to be repeatable with relative (RMSA-CV) intersession precision errors of 8%, 6%, 16% for full-thickness, superficial and deep cMFC ROIs, corresponding to absolute errors (SD) of 1.2, 1.5, 1.5 ms, respectively. In cMTP tissue, UTE-T2∗ relative repeatability was 8%, 8%, 13%, corresponding to absolute repeatability of 1.0, 1.5, 2.1 ms (full-thickness, superficial, deep). UTE-T2∗ values were higher in superficial cartilage compared to deep in both cMFC (P≪0.001) and cMTP (P=0.0004) regions. CONCLUSION: In vivo 3D UTE-T2∗ mapping at 3T is feasible and can be implemented using a standard clinical MRI scanner and knee coil. Intersession precision error of UTE-T2∗ values in full-thickness ROIs in the weight-bearing regions of asymptomatic subjects is under 1.2 ms or 8% (RMSA-CV). Significant zonal and regional variations of UTE-T2∗ were seen.

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。