Department of Oncology and Metabolism, The University of Sheffield, Sheffield, UK.
The Medical Research Council (MRC)-Arthritis Research UK Centre for Integrated Research into Musculoskeletal Ageing (CIMA), The University of Sheffield, Sheffield, UK.
J Bone Miner Res. 2022 Sep;37(9):1679-1688. doi: 10.1002/jbmr.4638. Epub 2022 Jul 15.
The risk of osteoporotic fracture is inversely related to bone mineral density (BMD), but how spatial BMD pattern influences fracture risk remains incompletely understood. This study used a pixel-level spatiotemporal atlas of proximal femoral BMD in 13,338 white European women (age 20-97 years) to quantitate age-related texture variation in BMD maps and generate a "reference" map of bone aging. We introduce a new index, called Densitometric Bone Age (DBA), as the age at which an individual site-specific BMD map (the proximal femur is studied here) best matches the median aging trajectory at that site in terms of the root mean squared error (RMSE). The ability of DBA to predict incident hip fracture and hip fracture pattern over 5 years following baseline BMD was compared against conventional region-based BMD analysis in a subset of 11,899 women (age 45-97 years), for which follow-up fracture records exist. There were 208 subsequent incident hip fractures in the study populations (138 femoral necks [FNs], 52 trochanteric [TR], 18 sites unspecified). DBA had modestly better performance compared to the conventional FN-BMD, TR-BMD, and total hip (TOT)-BMD in identifying hip fractures measured as the area under the curve (AUC) using receiver operating characteristics (ROC) curve analysis by 2% (95% confidence interval [CI], -0.5% to 3.5%), 3% (95% CI, 1.0% to 4.0%), and 1% (95% CI, 0.4% to 1.6%), respectively. Compared to FN-BMD T-score, DBA improved the ROC-AUC for predicting TR fractures by ~5% (95% CI, 1.1% to 9.8%) with similar performance in identifying FN fractures. Compared to TR-BMD T-score, DBA improved the ROC-AUC for the prediction of FN fractures by ~3% (95% CI, 1.1% to 4.9%), with similar performance in identifying TR fractures. Our findings suggest that DBA may provide a spatially sensitive measure of proximal femoral fragility that is not captured by FN-BMD or TR-BMD alone. © 2022 The Authors. Journal of Bone and Mineral Research published by Wiley Periodicals LLC on behalf of American Society for Bone and Mineral Research (ASBMR).
骨质疏松性骨折的风险与骨密度（BMD）呈负相关，但空间 BMD 模式如何影响骨折风险仍不完全清楚。本研究使用了 13338 名白种欧洲女性（年龄 20-97 岁）的股骨近端 BMD 像素级时空图谱，定量分析了 BMD 图谱中与年龄相关的纹理变化，并生成了“参考”骨龄图谱。我们引入了一个新的指数，称为密度计量骨龄（Densitometric Bone Age，DBA），作为个体特定部位 BMD 图谱（此处研究股骨近端）与该部位中位数老化轨迹之间的年龄，以均方根误差（Root Mean Squared Error，RMSE）为衡量标准。在存在基线 BMD 后 5 年内发生髋部骨折和髋部骨折模式的随访记录的 11899 名女性（年龄 45-97 岁）的亚组中，比较了 DBA 预测髋部骨折的能力，与传统的基于区域的 BMD 分析进行了比较。研究人群中发生 208 例后续髋部骨折（138 例股骨颈 [FN]，52 例转子间 [TR]，18 例部位不明）。使用接收器操作特征（Receiver Operating Characteristics，ROC）曲线分析，通过曲线下面积（Area Under the Curve，AUC）比较，DBA 在识别髋部骨折方面的表现略优于传统的 FN-BMD、TR-BMD 和全髋（Total Hip，TOT）-BMD，分别提高了 2%（95%置信区间 [Confidence Interval，CI]，-0.5%至 3.5%）、3%（95%CI，1.0%至 4.0%）和 1%（95%CI，0.4%至 1.6%）。与 FN-BMD T 评分相比，DBA 可改善预测 TR 骨折的 ROC-AUC 约 5%（95%CI，1.1%至 9.8%），对识别 FN 骨折的性能相似。与 TR-BMD T 评分相比，DBA 可改善预测 FN 骨折的 ROC-AUC 约 3%（95%CI，1.1%至 4.9%），对识别 TR 骨折的性能相似。我们的研究结果表明，DBA 可能提供一种对股骨近端脆弱性的空间敏感测量，而这是 FN-BMD 或 TR-BMD 单独测量无法捕捉到的。2022 年，作者。由 Wiley Periodicals LLC 代表美国骨骼与矿物质研究协会（American Society for Bone and Mineral Research，ASBMR）出版的《骨与矿物研究杂志》。
