Comparison of clinical semi-quantitative assessment of muscle fat infiltration with quantitative assessment using chemical shift-based water/fat separation in MR studies of the calf of post-menopausal women

比较临床半定量评估肌肉脂肪浸润与基于化学位移的水/脂肪分离法进行定量评估在绝经后妇女小腿磁共振研究中的效果

阅读:1

Abstract

OBJECTIVE: The goal of this study was to compare the semi-quantitative Goutallier classification for fat infiltration with quantitative fat-fraction derived from a magnetic resonance imaging (MRI) chemical shift-based water/fat separation technique. METHODS: Sixty-two women (age 61 ± 6 years), 27 of whom had diabetes, underwent MRI of the calf using a T1-weighted fast spin-echo sequence and a six-echo spoiled gradient-echo sequence at 3 T. Water/fat images and fat fraction maps were reconstructed using the IDEAL algorithm with T2* correction and a multi-peak model for the fat spectrum. Two radiologists scored fat infiltration on the T1-weighted images using the Goutallier classification in six muscle compartments. Spearman correlations between the Goutallier grades and the fat fraction were calculated; in addition, intra-observer and inter-observer agreement were calculated. RESULTS: A significant correlation between the clinical grading and the fat fraction values was found for all muscle compartments (P < 0.0001, R values ranging from 0.79 to 0.88). Goutallier grades 0-4 had a fat fraction ranging from 3.5 to 19%. Intra-observer and inter-observer agreement values of 0.83 and 0.81 were calculated for the semi-quantitative grading. CONCLUSION: Semi-quantitative grading of intramuscular fat and quantitative fat fraction were significantly correlated and both techniques had excellent reproducibility. However, the clinical grading was found to overestimate muscle fat. KEY POINTS: Fat infiltration of muscle commonly occurs in many metabolic and neuromuscular diseases. • Image-based semi-quantitative classifications for assessing fat infiltration are not well validated. • Quantitative MRI techniques provide an accurate assessment of muscle fat.

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。