Klintström Eva, Klintström Benjamin, Moreno Rodrigo, Brismar Torkel B, Pahr Dieter H, Smedby Örjan
Department of Medical and Health Science, Division of Radiology, Linköping University, Linköping, Sweden.
Center for medical Image Science and Visualization, Linköping University, Linköping, Sweden.
PLoS One. 2016 Aug 11;11(8):e0161101. doi: 10.1371/journal.pone.0161101. eCollection 2016.
Stiffness and shear moduli of human trabecular bone may be analyzed in vivo by finite element (FE) analysis from image data obtained by clinical imaging equipment such as high resolution peripheral quantitative computed tomography (HR-pQCT). In clinical practice today, this is done in the peripheral skeleton like the wrist and heel. In this cadaveric bone study, fourteen bone specimens from the wrist were imaged by two dental cone beam computed tomography (CBCT) devices and one HR-pQCT device as well as by dual energy X-ray absorptiometry (DXA). Histomorphometric measurements from micro-CT data were used as gold standard. The image processing was done with an in-house developed code based on the automated region growing (ARG) algorithm. Evaluation of how well stiffness (Young's modulus E3) and minimum shear modulus from the 12, 13, or 23 could be predicted from the CBCT and HR-pQCT imaging data was studied and compared to FE analysis from the micro-CT imaging data. Strong correlations were found between the clinical machines and micro-CT regarding trabecular bone structure parameters, such as bone volume over total volume, trabecular thickness, trabecular number and trabecular nodes (varying from 0.79 to 0.96). The two CBCT devices as well as the HR-pQCT showed the ability to predict stiffness and shear, with adjusted R2-values between 0.78 and 0.92, based on data derived through our in-house developed code based on the ARG algorithm. These findings indicate that clinically used CBCT may be a feasible method for clinical studies of bone structure and mechanical properties in future osteoporosis research.
人体小梁骨的硬度和剪切模量可通过有限元（FE）分析在体内进行分析，该分析基于从临床成像设备（如高分辨率外周定量计算机断层扫描（HR-pQCT））获得的图像数据。在当今的临床实践中，这是在手腕和脚跟等外周骨骼部位进行的。在这项尸体骨研究中，来自手腕的14个骨标本通过两台牙科锥形束计算机断层扫描（CBCT）设备、一台HR-pQCT设备以及双能X射线吸收法（DXA）进行成像。来自微型CT数据的组织形态计量学测量被用作金标准。图像处理使用基于自动区域生长（ARG）算法的内部开发代码完成。研究了从CBCT和HR-pQCT成像数据预测12、13或23处的硬度（杨氏模量E3）和最小剪切模量的效果，并与微型CT成像数据的有限元分析进行比较。在小梁骨结构参数方面，如骨体积占总体积的比例、小梁厚度、小梁数量和小梁节点，临床机器与微型CT之间发现了强相关性（相关系数在0.79至0.96之间）。两台CBCT设备以及HR-pQCT均显示出预测硬度和剪切的能力，基于通过我们基于ARG算法的内部开发代码得出的数据，调整后的R2值在0.78至0.92之间。这些发现表明，临床使用的CBCT可能是未来骨质疏松症研究中骨结构和力学性能临床研究的一种可行方法。
