Li Wenjun, Kornak John, Harris Tamara, Keyak Joyce, Li Caixia, Lu Ying, Cheng Xiaoguang, Lang Thomas
Department of Radiology, University of California, San Francisco, San Francisco, CA 94143, USA.
Bone. 2009 Apr;44(4):596-602. doi: 10.1016/j.bone.2008.12.008. Epub 2008 Dec 24.
We identified regions inside the proximal femur that are most strongly associated with hip fracture. Bone densitometry based on such fracture-critical regions showed improved power in discriminating fracture patients from controls.
Hip fractures typically occur in lateral falls, with focal mechanical failure of the sub-volumes of tissue in which the applied stress exceeds the strength. In this study, we describe a new methodology to identify proximal femoral tissue elements with highest association with hip fracture. We hypothesize that bone mineral density (BMD) measured in such sub-volumes discriminates hip fracture risk better than BMD in standard anatomic regions such as the femoral neck and trochanter.
We employed inter-subject registration to transform hip QCT images of 37 patients with hip fractures and 38 age-matched controls into a voxel-based statistical atlas. Within voxels, we performed t-tests between the two groups to identify the regions which differed most. We then randomly divided the 75 scans into a training set and a test set. From the training set, we derived a fracture-driven region of interest (ROI) based on association with fracture. In the test set, we measured BMD in this ROI to determine fracture discrimination efficacy using ROC analysis. Additionally, we compared the BMD distribution differences between the 29 patients with neck fractures and the 8 patients with trochanteric fractures.
By evaluating fracture discrimination power based on ROC analysis, the fracture-driven ROI had an AUC (area under curve) of 0.92, while anatomic ROIs (including the entire proximal femur, the femoral neck, trochanter and their cortical and trabecular compartments) had AUC values between 0.78 and 0.87. We also observed that the neck fracture patients had lower BMD (p=0.014) in a small region near the femoral neck and the femoral head, and patients with trochanteric fractures had lower BMD in trochanteric regions such as in the internal calcar septum (p=0.006).
We have identified the sub-volumes of proximal femoral tissue which have the strongest association with hip fracture. The power to predict fracture can be improved, by focusing on BMD measurements in the fracture-critical regions, rather than in standard ROIs.
我们确定了股骨近端与髋部骨折关联最为密切的区域。基于此类骨折关键区域的骨密度测量在区分骨折患者与对照组方面显示出更高的效能。
髋部骨折通常发生在侧方跌倒时,施加应力超过强度的组织亚体积会出现局部机械性失效。在本研究中,我们描述了一种新方法,用于识别与髋部骨折关联度最高的股骨近端组织成分。我们假设,在此类亚体积中测量的骨矿物质密度(BMD)比在股骨颈和大转子等标准解剖区域测量的BMD能更好地鉴别髋部骨折风险。
我们采用受试者间配准,将37例髋部骨折患者和38例年龄匹配的对照组的髋部定量CT图像转换为基于体素的统计图谱。在体素内,我们在两组之间进行t检验以识别差异最大的区域。然后我们将75次扫描随机分为训练集和测试集。从训练集中,我们基于与骨折的关联得出骨折驱动的感兴趣区域(ROI)。在测试集中,我们在该ROI中测量BMD,以使用ROC分析确定骨折鉴别效能。此外,我们比较了29例颈部骨折患者和8例转子间骨折患者之间的BMD分布差异。
通过基于ROC分析评估骨折鉴别效能,骨折驱动的ROI的曲线下面积(AUC)为0.92,而解剖学ROI(包括整个股骨近端、股骨颈、大转子及其皮质和小梁部分)的AUC值在0.78至0.87之间。我们还观察到,颈部骨折患者在股骨颈和股骨头附近的一个小区域内BMD较低(p = 0.014),转子间骨折患者在转子间区域如内髁间嵴处BMD较低(p = 0.006)。
我们已经确定了股骨近端组织中与髋部骨折关联最强的亚体积。通过关注骨折关键区域而非标准ROI中的BMD测量,可以提高预测骨折的效能。