Dual-energy X-ray absorptiometry derived knee shape may provide a useful imaging biomarker for predicting total knee replacement: Findings from a study of 37,843 people in UK Biobank

Rhona A. Beynon , Fiona R. Saunders , Raja Ebsim , Monika Frysz , Benjamin G. Faber , Jennifer S. Gregory , Claudia Lindner , Aliya Sarmanova , Richard M. Aspden , Nicholas C. Harvey , Timothy Cootes , Jonathan H. Tobias
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引用次数: 0

Abstract

Objective

We aimed to create an imaging biomarker for knee shape using knee dual-energy x-ray absorptiometry (DXA) scans and investigate its potential association with subsequent total knee replacement (TKR), independently of radiographic features of knee osteoarthritis and established risk factors.

Methods

Using a 129-point statistical shape model, knee shape (expressed as a B-score) and minimum joint space width (mJSW) of the medial joint compartment (binarized as above or below the first quartile) were derived. Osteophytes were manually graded in a subset of images and an overall score was assigned. Cox proportional hazards models were used to examine the associations of B-score, mJSW and osteophyte score with TKR risk, adjusting for age, sex, height and weight.

Results

The analysis included 37,843 individuals (mean age 63.7 years). In adjusted models, B-score was associated with TKR: each unit increase in B-score, reflecting one standard deviation from the mean healthy shape, corresponded to a hazard ratio (HR) of 2.25 (2.08, 2.43), while a lower mJSW had a HR of 2.28 (1.88, 2.77). Among the 6719 images scored for osteophytes, mJSW was replaced by osteophyte score in the most strongly predictive model for TKR. In ROC analyses, a model combining B-score, osteophyte score, and demographics outperformed a model including demographics alone (AUC ​= ​0.87 vs 0.73).

Conclusions

Using statistical shape modelling, we derived a DXA-based imaging biomarker for knee shape that was associated with kOA progression. When combined with osteophytes and demographic data, this biomarker may help identify individuals at high risk of TKR, facilitating targeted interventions.

双能 X 射线吸收测量法得出的膝关节形状可为预测全膝关节置换术提供有用的成像生物标志物:英国生物库中 37,843 人的研究结果
方法使用 129 点统计形状模型,得出膝关节形状(以 B 分数表示)和内侧关节腔的最小关节间隙宽度(mJSW)(二值化为高于或低于第一四分位数)。对部分图像进行人工分级,并给出总分。在对年龄、性别、身高和体重进行调整后,使用 Cox 比例危险模型来检验 B-评分、mJSW 和骨质增生评分与 TKR 风险的相关性。在调整后的模型中,B-评分与 TKR 相关:B-评分每增加一个单位,即与平均健康形态相比增加一个标准差,其危险比 (HR) 为 2.25(2.08, 2.43),而 mJSW 越低,其危险比为 2.28(1.88, 2.77)。在 6 719 张骨质增生评分图像中,骨质增生评分取代了 mJSW 成为预测 TKR 最有力的模型。在 ROC 分析中,结合 B 评分、骨质增生评分和人口统计学特征的模型优于仅包含人口统计学特征的模型(AUC = 0.87 vs 0.73)。当与骨质增生和人口统计学数据相结合时,该生物标志物可能有助于识别TKR高风险人群,从而进行有针对性的干预。
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来源期刊
Osteoarthritis and cartilage open
Osteoarthritis and cartilage open Orthopedics, Sports Medicine and Rehabilitation
CiteScore
3.30
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