Abstract：
Areal bone mineral density (aBMD) currently represents the clinical gold standard for hip fracture risk assessment. Nevertheless, it is characterised by a limited prediction accuracy, as about half of the people experiencing a fracture are not classified as at being at risk by aBMD. In the context of a progressively ageing population, the identification of accurate predictive tools would be pivotal to implement preventive actions. In this study, DXA-based statistical models of the proximal femur shape, intensity (i.e., density) and their combination were developed and employed to predict hip fracture on a retrospective cohort of post-menopausal women. Proximal femur shape and pixel-by-pixel aBMD values were extracted from DXA images and partial least square (PLS) algorithm adopted to extract corresponding modes and components. Subsequently, logistic regression models were built employing the first three shape, intensity and shape-intensity PLS components, and their ability to predict hip fracture tested according to a 10-fold cross-validation procedure. The area under the ROC curves (AUC) for the shape, intensity, and shape-intensity-based predictive models were 0.59 (95%CI 0.47-0.69), 0.80 (95%CI 0.70-0.90) and 0.83 (95%CI 0.73-0.90), with the first being significantly lower than the latter two. aBMD yielded an AUC of 0.72 (95%CI 0.59-0.82), found to be significantly lower than the shape-intensity-based predictive model. In conclusion, a methodology to assess hip fracture risk uniquely based on the clinically available imaging technique, DXA, is proposed. Our study results show that hip fracture risk prediction could be enhanced by taking advantage of the full set of information DXA contains.
摘要：
Areal骨矿物质密度（aBMD）目前是髋部骨折风险评估的临床金标准。然而，它的特点是预测精度有限，因为大约一半的骨折患者没有被aBMD分类为有风险。在人口逐渐老龄化的背景下,确定准确的预测工具对于实施预防措施至关重要。在这项研究中,基于DXA的股骨近端形状统计模型，强度(即，密度）及其组合被开发并用于预测绝经后妇女的回顾性队列中的髋部骨折。从DXA图像中提取股骨近端形状和逐像素aBMD值，并采用偏最小二乘（PLS）算法提取相应的模式和分量。随后，采用前三种形状建立逻辑回归模型，强度和形状强度PLS分量，以及根据10倍交叉验证程序测试其预测髋部骨折的能力。形状的ROC曲线下面积（AUC），强度,基于形状强度的预测模型为0.59(95CI0.47-0.69)，0.80（95CI0.70-0.90）和0.83（95CI0.73-0.90），前者明显低于后两者。aBMD的AUC为0.72(95CI0.59-0.82)，发现明显低于基于形状强度的预测模型。总之,一种基于临床可用的成像技术评估髋部骨折风险的方法，DXA,是提议的。我们的研究结果表明，利用DXA包含的全套信息可以增强髋部骨折风险预测。
