Objective

To evaluate the agreement, accuracy, and longitudinal reproducibility of quantitative cartilage morphometry from 2D U-Net-based automated segmentations for 3T coronal fast low angle shot (corFLASH) and sagittal double echo at steady-state (sagDESS) MRI.

Methods

2D U-Nets were trained using manual, quality-controlled femorotibial cartilage segmentations available for 92 Osteoarthritis Initiative healthy reference cohort participants from both corFLASH and sagDESS (n = 50/21/21 training/validation/test-set). Cartilage morphometry was computed from automated and manual segmentations for knees from the test-set. Agreement and accuracy were evaluated from baseline visits (dice similarity coefficient: DSC, correlation analysis, systematic offset). The longitudinal reproducibility was assessed from year-1 and -2 follow-up visits (root-mean-squared coefficient of variation, RMSCV%).

Results

Automated segmentations showed high agreement (DSC 0.89–0.92) and high correlations (r ≥ 0.92) with manual ground truth for both corFLASH and sagDESS and only small systematic offsets (≤ 10.1%). The automated measurements showed a similar test–retest reproducibility over 1 year (RMSCV% 1.0–4.5%) as manual measurements (RMSCV% 0.5–2.5%).

Discussion

The 2D U-Net-based automated segmentation method yielded high agreement compared with manual segmentation and also demonstrated high accuracy and longitudinal test–retest reproducibility for morphometric analysis of articular cartilage derived from it, using both corFLASH and sagDESS.

中文翻译：

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基于 U-Net 自动分割两种不同 MRI 对比的定量股胫软骨测量的准确性和纵向可重复性：来自骨关节炎倡议健康参考队列的数据

客观的

评估来自基于 2D U-Net 的自动分割的定量软骨形态测量的一致性、准确性和纵向可重复性，用于 3T 冠状快速低角度拍摄 (corFLASH) 和稳态 (sagDESS) MRI 下的矢状双回波。

方法

2D U-Nets 使用手动、质量控制的股胫软骨分割进行训练，可用于来自 corFLASH 和 sagDESS 的 92 名骨关节炎倡议健康参考队列参与者（n  = 50/21/21 训练/验证/测试集）。软骨形态测量是根据来自测试集的膝盖的自动和手动分割计算的。从基线访问（骰子相似系数：DSC、相关分析、系统偏移）评估一致性和准确性。从第 1 年和第 -2 年的随访中评估纵向再现性（均方根变异系数，RMSCV%）。

结果

自动分割 与 corFLASH 和 sagDESS 的手动地面实况显示出高一致性 (DSC 0.89–0.92) 和高相关性 ( r ≥ 0.92)，并且只有很小的系统偏移 (≤ 10.1%)。自动测量显示了与手动测量 (RMSCV% 0.5–2.5%) 相似的 1 年重测重现性 (RMSCV% 1.0–4.5%)。

讨论

与手动分割相比，基于 2D U-Net 的自动分割方法产生了很高的一致性，并且还展示了使用 corFLASH 和 sagDESS 对其衍生的关节软骨进行形态测量分析的高精度和纵向测试 - 重测可重复性。