Objective

The goal of this study was to assess the reproducibility of an automated knee cartilage segmentation of 21 cartilage regions with a model-based algorithm and to compare the results with manual segmentation.

Design

Thirteen patients with low-grade femoral cartilage defects were included in the study and were scanned twice on a 7-T magnetic resonance imaging (MRI) scanner 8 days apart. A 3-dimensional double-echo steady-state (3D-DESS) sequence was used to acquire MR images for automated cartilage segmentation, and T2-mapping was performed using a 3D triple-echo steady-state (3D-TESS) sequence. Cartilage volume, thickness, and T2 and texture features were automatically extracted from each knee for each of the 21 subregions. DESS was used for manual cartilage segmentation and compared with automated segmentation using the Dice coefficient. The reproducibility of each variable was expressed using standard error of measurement (SEM) and smallest detectable change (SDC).

Results

The Dice coefficient for the similarity between manual and automated segmentation ranged from 0.83 to 0.88 in different cartilage regions. Test-retest analysis of automated cartilage segmentation and automated quantitative parameter extraction revealed excellent reproducibility for volume measurement (mean SDC for all subregions of 85.6 mm³), for thickness detection (SDC = 0.16 mm) and also for T2 values (SDC = 2.38 ms) and most gray-level co-occurrence matrix features (SDC = 0.1 a.u.).

Conclusions

The proposed technique of automated knee cartilage evaluation based on the segmentation of 3D MR images and correlation with T2 mapping provides highly reproducible results and significantly reduces the segmentation effort required for the analysis of knee articular cartilage in longitudinal studies.

中文翻译：

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低级别膝关节软骨损伤的自动定量 MRI 评估的可重复性

客观的

本研究的目的是评估使用基于模型的算法对 21 个软骨区域进行自动膝关节软骨分割的可重复性，并将结果与​​手动分割进行比较。

设计

13 名患有低度股骨软骨缺损的患者被纳入研究，并在 7-T 磁共振成像 (MRI) 扫描仪上扫描两次，间隔 8 天。使用 3 维双回波稳态 (3D-DESS) 序列获取用于自动软骨分割的 MR 图像，并使用 3D 三重回波稳态 (3D-TESS) 序列进行 T2 映射。对于 21 个子区域中的每一个，从每个膝关节自动提取软骨体积、厚度、T2 和纹理特征。DESS 用于手动软骨分割，并与使用 Dice 系数的自动分割进行比较。使用标准测量误差 (SEM) 和最小可检测变化 (SDC) 表示每个变量的重现性。

结果

在不同的软骨区域，手动和自动分割之间相似性的 Dice 系数在 0.83 到 0.88 之间。自动软骨分割和自动定量参数提取的重测分析揭示了体积测量（85.6 mm ³所有子区域的平均 SDC ）、厚度检测（SDC = 0.16 mm）和 T2 值（SDC = 2.38 ms）的出色再现性) 和大多数灰度共生矩阵特征 (SDC = 0.1 au)。

结论

所提出的基于 3D MR 图像分割和与 T2 映射相关性的自动膝关节软骨评估技术提供了高度可重复的结果，并显着减少了纵向研究中膝关节软骨分析所需的分割工作。