Whitmarsh Tristan, Fritscher Karl D, Humbert Ludovic, Del Rio Barquero Luís Miguel, Roth Tobias, Kammerlander Christian, Blauth Michael, Schubert Rainer, Frangi Alejandro F
Center for Computational Imaging & Simulation Technologies in Biomedicine (CISTIB), Universitat Pompeu Fabra (UPF) and CIBER-BBN, Barcelona, Spain.
Med Image Comput Comput Assist Interv. 2011;14(Pt 2):393-400. doi: 10.1007/978-3-642-23629-7_48.
This work presents a statistical model of both the shape and Bone Mineral Density (BMD) distribution of the proximal femur for fracture risk assessment. The shape and density model was built from a dataset of Quantitative Computed Tomography scans of fracture patients and a control group. Principal Component Analysis and Horn's parallel analysis were used to reduce the dimensionality of the shape and density model to the main modes of variation. The input data was then used to analyze the model parameters for the optimal separation between the fracture and control group. Feature selection using the Fisher criterion determined the parameters with the best class separation, which were used in Fisher Linear Discriminant Analysis to find the direction in the parameter space that best separates the fracture and control group. This resulted in a Fisher criterion value of 6.70, while analyzing the Dual-energy X-ray Absorptiometry derived femur neck areal BMD of the same subjects resulted in a Fisher criterion value of 0.98. This indicates that a fracture risk estimation approach based on the presented model might improve upon the current standard clinical practice.
这项工作提出了一种用于骨折风险评估的股骨近端形状和骨矿物质密度（BMD）分布的统计模型。该形状和密度模型是基于骨折患者和对照组的定量计算机断层扫描数据集构建的。主成分分析和霍恩平行分析用于将形状和密度模型的维度降低到主要变化模式。然后使用输入数据来分析模型参数，以实现骨折组和对照组之间的最佳分离。使用费希尔准则进行特征选择确定了具有最佳类别分离效果的参数，这些参数用于费希尔线性判别分析，以找到参数空间中最能区分骨折组和对照组的方向。结果得到费希尔准则值为6.70，而分析同一受试者的双能X线吸收法得出的股骨颈面积BMD时，费希尔准则值为0.98。这表明基于所提出模型的骨折风险估计方法可能优于当前的标准临床实践。
