Machine-learning, MRI bone shape and important clinical outcomes in osteoarthritis: data from the Osteoarthritis Initiative.
Machine-learning, MRI bone shape and important clinical outcomes in osteoarthritis: data from the Osteoarthritis Initiative.
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DOI：
10.1136/annrheumdis-2020-217160
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发表时间：
2021-04
影响因子：
27.4
通讯作者：
Conaghan PG
中科院分区：
文献类型：
--
作者：
Bowes MA;Kacena K;Alabas OA;Brett AD;Dube B;Bodick N;Conaghan PG
骨关节炎(OA)的结构状态不能用放射学评估来分类。统计形状建模(SSM)是机器学习的一种形式，它提供了对典型的3D OA骨骼形状的精确量化。我们的目标是确定这种新的骨性关节炎状态测量方法在评估临床重要结果的风险方面的益处。这项研究使用了来自骨关节炎倡议队列的4796名个人。从所有9433个基线膝关节磁共振成像中测量SSM衍生的股骨骨形状(B-Score)。我们研究了B评分、放射学Kellgren-Lawrence分级(KLG)与当前和未来疼痛和功能以及长达8年的全膝关节置换术(TKR)的关系。B分可重复性支持40个不同的等级。KLG和B评分均与当前和未来疼痛风险、功能受限和TKR相关；Logistic回归曲线相似。然而，每个KLG都包含了广泛的B分。例如，对于KLG3，疼痛的风险为34.4(95%可信区间31.7~37.0)%，但KLG3膝关节内的B评分范围为0~6；B评分0的风险为17.0(16.1~17.9)%，而B评分6的风险为52.1(48.8~55.4)%。对于TKR，KLG3风险为15.3(13.3~17.3)%，B评分0可忽略风险，B评分6风险为35.6(31.8~39.6)%。年龄、性别和体重指数对B分数和症状之间的关联影响很小。B-SCORE使用单个时间点提供独立于读者的量化，提供明确的OA状态以及整个疾病范围内明确的临床风险，包括放射检查前的OA。B评分预示着干预措施的OA分层和改进的个性化评估的阶梯变化，类似于骨质疏松症的T评分。
Osteoarthritis (OA) structural status is imperfectly classified using radiographic assessment. Statistical shape modelling (SSM), a form of machine-learning, provides precise quantification of a characteristic 3D OA bone shape. We aimed to determine the benefits of this novel measure of OA status for assessing risks of clinically important outcomes. The study used 4796 individuals from the Osteoarthritis Initiative cohort. SSM-derived femur bone shape (B-score) was measured from all 9433 baseline knee MRIs. We examined the relationship between B-score, radiographic Kellgren-Lawrence grade (KLG) and current and future pain and function as well as total knee replacement (TKR) up to 8 years. B-score repeatability supported 40 discrete grades. KLG and B-score were both associated with risk of current and future pain, functional limitation and TKR; logistic regression curves were similar. However, each KLG included a wide range of B-scores. For example, for KLG3, risk of pain was 34.4 (95% CI 31.7 to 37.0)%, but B-scores within KLG3 knees ranged from 0 to 6; for B-score 0, risk was 17.0 (16.1 to 17.9)% while for B-score 6, it was 52.1 (48.8 to 55.4)%. For TKR, KLG3 risk was 15.3 (13.3 to 17.3)%; while B-score 0 had negligible risk, B-score 6 risk was 35.6 (31.8 to 39.6)%. Age, sex and body mass index had negligible effects on association between B-score and symptoms. B-score provides reader-independent quantification using a single time-point, providing unambiguous OA status with defined clinical risks across the whole range of disease including pre-radiographic OA. B-score heralds a step-change in OA stratification for interventions and improved personalised assessment, analogous to the T-score in osteoporosis.
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影响因子：
10.6
作者：
Williams, Tomos G.;Holmes, Andrew P.;Taylor, Chris J.
通讯作者：
Taylor, Chris J.
DOI：
10.1038/s41584-018-0010-z
发表时间：
2018-06
期刊：
Nature reviews. Rheumatology
影响因子：
--
作者：
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通讯作者：
Guermazi A
影响因子：
27.4
作者：
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通讯作者：
Dekker, Joost
影响因子：
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作者：
Guermazi, Ali;Roemer, Frank W.;Brandt, Kenneth D.
通讯作者：
Brandt, Kenneth D.
影响因子：
7
作者：
Peterfy CG;Schneider E;Nevitt M
通讯作者：
Nevitt M