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Predicting Trabecular Bone Stiffness from Clinical Cone-Beam CT and HR-pQCT Data; an In Vitro Study Using Finite Element Analysis

机译:根据临床锥形束CT和HR-pQCT数据预测小梁骨刚度;有限元分析的体外研究

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摘要

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.
机译:人体小梁骨的刚度和剪切模量可以通过有限元(FE)分析,从临床成像设备(如高分辨率外围定量X线断层扫描(HR-pQCT))获得的图像数据进行体内分析。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。在这个尸体骨研究中,通过两个牙科锥束计算机断层扫描(CBCT)设备和一个HR-pQCT设备以及双能X射线吸收法(DXA)对来自手腕的14个骨标本进行了成像。来自微型CT数据的组织形态测量结果用作金标准。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。通过CBCT和HR-pQCT成像数据评估了如何预测12、13或23的刚度(杨氏模量E3)和最小剪切模量,并进行了评估,并将其与微型CT成像数据中的有限元分析进行了比较。在骨小梁的骨结构参数(例如骨体积占总体积,骨小梁厚度,骨小梁数目和骨小梁结)(从0.79到0.96)之间,临床机器和微型CT之间发现了很强的相关性。根据通过我们内部开发的代码得出的数据,这两种CBCT设备以及HR-pQCT均具有预测刚度和剪切力的能力,其R 2 值在0.78至0.92之间调整在ARG算法上。这些发现表明,在未来的骨质疏松症研究中,临床使用的CBCT可能是进行骨结构和力学性能临床研究的可行方法。

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