Predicting Trabecular Bone Stiffness from Clinical Cone-Beam CT and HR-pQCT Data; an In Vitro Study Using Finite Element Analysis
Predicting Trabecular Bone Stiffness from Clinical Cone-Beam CT and HR-pQCT Data; an In Vitro Study Using Finite Element Analysis
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DOI：
10.1371/journal.pone.0161101
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发表时间：
2016-08-11
期刊：
影响因子：
3.7
通讯作者：
Smedby, Orjan
中科院分区：
文献类型：
--
作者：
Klintstrom, Eva;Klintstrom, Benjamin;Smedby, Orjan
人体小梁骨的刚度和剪切模量可以通过有限元（FE）分析来体内分析，该有限元分析来自临床成像设备（例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围骨骼中完成的。在这项尸体骨骼研究中，通过两台牙科锥形束计算机断层扫描 (CBCT) 设备和一台 HR-pQCT 设备以及双能 X 射线吸收测定法 (DXA) 对来自手腕的 14 个骨骼样本进行了成像。来自显微 CT 数据的组织形态测量被用作金标准。图像处理是使用基于自动区域生长（ARG）算法的内部开发代码完成的。研究了如何根据 CBCT 和 HR-pQCT 成像数据预测刚度（杨氏模量 E3）和最小剪切模量 12、13 或 23，并与根据显微 CT 成像数据进行的有限元分析进行比较。临床机器和显微 CT 之间的小梁骨结构参数（例如骨体积占总体积、小梁厚度、小梁数量和小梁节点（从 0.79 到 0.96 不等））之间存在很强的相关性。两个 CBCT 设备以及 HR-pQCT 显示了预测刚度和剪切力的能力，根据我们基于 ARG 算法的内部开发代码得出的数据，调整后的 R-2 值在 0.78 和 0.92 之间。这些结果表明，临床上使用的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可行方法。
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 R-2-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.