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结合磁共振T2和三维快速自旋回波图像的髋关节软骨自动分析

Automated analysis of hip joint cartilage combining MR T2 and three-dimensional fast-spin-echo images.

作者信息

Chandra Shekhar S, Surowiec Rachel, Ho Charles, Xia Ying, Engstrom Craig, Crozier Stuart, Fripp Jurgen

机构信息

School of Information Technology and Electrical Engineering, University of Queensland, Australia.

Steadman Philippon Research Institute (SPRI), Colorado, USA.

出版信息

Magn Reson Med. 2016 Jan;75(1):403-13. doi: 10.1002/mrm.25598. Epub 2015 Jan 30.

Abstract

PURPOSE

To validate a fully automated scheme to extract biochemical information from the hip joint cartilages using MR T2 mapping images incorporating segmentation of co-registered three-dimensional Fast-Spin-Echo (3D-SPACE) images.

METHODS

Manual analyses of unilateral hip (3 Tesla) MR images of 24 asymptomatic volunteers were used to validate a 3D deformable model method for automated cartilage segmentation of SPACE scans, partitioning of the individual femoral and acetabular cartilage plates into clinically defined sub-regions and propagating these results to T2 maps to calculate region-wise T2 value statistics. Analyses were completed on a desktop computer (∼ 10 min per case).

RESULTS

The mean voxel overlap between automated A and manual M segmentations of the cartilage volumes in the (clinically based) SPACE images was 73% (100 × 2|A∩M|/[|A|+|M|]). The automated and manual analyses demonstrated a relative difference error <10% in the median "T2 average signal" for each cartilage plate. The automated and manual analyses showed consistent patterns between significant differences in T2 data across the hip cartilage sub-regions.

CONCLUSION

The good agreement between the manual and automatic analyses of T2 values indicates the use of structural 3D-SPACE MR images with the proposed method provides a promising approach for automated quantitative T2 assessment of hip joint cartilages.

摘要

目的

验证一种全自动方案,该方案利用磁共振T2映射图像(结合共配准的三维快速自旋回波(3D-SPACE)图像的分割)从髋关节软骨中提取生化信息。

方法

对24名无症状志愿者的单侧髋关节(3特斯拉)磁共振图像进行手动分析,以验证一种用于SPACE扫描自动软骨分割的三维可变形模型方法,将单个股骨和髋臼软骨板划分为临床定义的子区域,并将这些结果传播到T2图,以计算区域T2值统计数据。分析在台式计算机上完成(每个病例约10分钟)。

结果

在(基于临床的)SPACE图像中,软骨体积的自动分割A与手动分割M之间的平均体素重叠率为73%(100×2|A∩M|/[|A|+|M|])。自动分析和手动分析表明,每个软骨板的“T2平均信号”中位数的相对差异误差<10%。自动分析和手动分析显示,髋关节软骨子区域的T2数据的显著差异之间存在一致的模式。

结论

T2值的手动分析与自动分析之间的良好一致性表明,使用结构3D-SPACE磁共振图像和所提出的方法为髋关节软骨的自动定量T2评估提供了一种有前景的方法。

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