T2analysis of the entire osteoarthritis initiative dataset
T2analysis of the entire osteoarthritis initiative dataset
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DOI：
10.1002/jor.24811
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发表时间：
2020-07-27
影响因子：
2.8
通讯作者：
Pedoia, Valentina
中科院分区：
文献类型：
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作者：
Razmjoo, Alaleh;Caliva, Francesco;Pedoia, Valentina
虽然已经做了大量的工作来了解软骨T(2)松弛时间与骨关节炎（OA）之间的关系，但T(2)在大量人群中的诊断和预后能力仍有待建立。利用3921人工标注的二维多层多回波自旋回波磁共振成像体，建立了用于膝关节软骨自动分割的分割模型并进行了评价。然后使用优化后的模型计算整个骨关节炎倡议（OAI）数据集的T(2)值，该数据集由4796个独特患者的纵向采集组成，共25 729个磁共振成像研究。在整个OAI数据集中分析了T(2)值、OA危险因素、影像学OA和疼痛之间的横断面关系。我们还探讨了T(2)值在预测未来放射学OA发病率和全膝关节置换术（TKR）中的作用。自动T(2)值与手动T(2)值相当。发现T(2)放松时间与人口学和临床变量之间存在显著关联。胫骨-股骨T(2)值最高25%的受试者2年后患骨性关节炎的风险高出5倍。内侧股骨T(2)值升高与5年后TKR显著相关（coeff = 0.10;P = 0.036; CI =[0.01,0.20]）。我们的研究强化了T(2)对未来OA和TKR发病率的预测价值。与仅使用人口统计学和临床变量相比，自动分割模型中包含的T(2)平均值改善了几个评估指标。
While substantial work has been done to understand the relationships between cartilage T(2)relaxation times and osteoarthritis (OA), diagnostic and prognostic abilities of T(2)on a large population yet need to be established. Using 3921 manually annotated 2D multi-slice multi-echo spin-echo magnetic resonance imaging volume, a segmentation model for automatic knee cartilage segmentation was built and evaluated. The optimized model was then used to calculate T(2)values on the entire osteoarthritis initiative (OAI) dataset composed of longitudinal acquisitions of 4796 unique patients, 25 729 magnetic resonance imaging studies in total. Cross-sectional relationships between T(2)values, OA risk factors, radiographic OA, and pain were analyzed in the entire OAI dataset. The performance of T(2)values in predicting the future incidence of radiographic OA as well as total knee replacement (TKR) were also explored. Automatic T(2)values were comparable with manual ones. Significant associations between T(2)relaxation times and demographic and clinical variables were found. Subjects in the highest 25% quartile of tibio-femoral T(2)values had a five times higher risk of radiographic OA incidence 2 years later. Elevation of medial femur T(2)values was significantly associated with TKR after 5 years (coeff = 0.10;P = .036; CI = [0.01,0.20]). Our investigation reinforces the predictive value of T(2)for future incidence OA and TKR. The inclusion of T(2)averages from the automatic segmentation model improved several evaluation metrics when compared to only using demographic and clinical variables.