Giambini Hugo, Dragomir-Daescu Dan, Nassr Ahmad, Yaszemski Michael J, Zhao Chunfeng
J Biomech Eng. 2016 Sep 1;138(9):0910031-7. doi: 10.1115/1.4034172.
Quantitative computed tomography-based finite-element analysis (QCT/FEA) has become increasingly popular in an attempt to understand and possibly reduce vertebral fracture risk. It is known that scanning acquisition settings affect Hounsfield units (HU) of the CT voxels. Material properties assignments in QCT/FEA, relating HU to Young's modulus, are performed by applying empirical equations. The purpose of this study was to evaluate the effect of QCT scanning protocols on predicted stiffness values from finite-element models. One fresh frozen cadaveric torso and a QCT calibration phantom were scanned six times varying voltage and current and reconstructed to obtain a total of 12 sets of images. Five vertebrae from the torso were experimentally tested to obtain stiffness values. QCT/FEA models of the five vertebrae were developed for the 12 image data resulting in a total of 60 models. Predicted stiffness was compared to the experimental values. The highest percent difference in stiffness was approximately 480% (80 kVp, 110 mAs, U70), while the lowest outcome was ∼1% (80 kVp, 110 mAs, U30). There was a clear distinction between reconstruction kernels in predicted outcomes, whereas voltage did not present a clear influence on results. The potential of QCT/FEA as an improvement to conventional fracture risk prediction tools is well established. However, it is important to establish research protocols that can lead to results that can be translated to the clinical setting.
基于定量计算机断层扫描的有限元分析(QCT/FEA)在试图理解并可能降低椎体骨折风险方面越来越受欢迎。众所周知,扫描采集设置会影响CT体素的亨氏单位(HU)。在QCT/FEA中,通过应用经验方程来进行将HU与杨氏模量相关联的材料属性赋值。本研究的目的是评估QCT扫描协议对有限元模型预测刚度值的影响。对一具新鲜冷冻的尸体躯干和一个QCT校准体模进行了六次扫描,改变电压和电流,并进行重建以获得总共12组图像。对躯干中的五块椎骨进行了实验测试以获得刚度值。针对这12组图像数据建立了这五块椎骨的QCT/FEA模型,总共得到60个模型。将预测的刚度与实验值进行比较。刚度的最大百分比差异约为480%(80 kVp,110 mAs,U70),而最低结果约为1%(80 kVp,110 mAs,U30)。在预测结果中,重建内核之间存在明显差异,而电压对结果没有明显影响。QCT/FEA作为对传统骨折风险预测工具的改进的潜力已得到充分证实。然而,建立能够得出可转化到临床环境的结果的研究方案很重要。