Laboratory for Structural NMR Imaging, Department of Radiology, University of Pennsylvania Medical Center, 3400 Spruce St, Philadelphia, PA 19104.
Acad Radiol. 2013 Dec;20(12):1584-91. doi: 10.1016/j.acra.2013.09.005.
To assess the performance of a nonlinear microfinite element model on predicting trabecular bone yield and post-yield behavior based on high-resolution in vivo magnetic resonance images via the serial reproducibility.
The nonlinear model captures material nonlinearity by iteratively adjusting tissue-level modulus based on tissue-level effective strain. It enables simulations of trabecular bone yield and post-yield behavior from micro magnetic resonance images at in vivo resolution by solving a series of nonlinear systems via an iterative algorithm on a desktop computer. Measures of mechanical competence (yield strain/strength, ultimate strain/strength, modulus of resilience, and toughness) were estimated at the distal radius of premenopausal and postmenopausal women (N = 20, age range 50-75) in whom osteoporotic fractures typically occur. Each subject underwent three scans (20.2 ± 14.5 days). Serial reproducibility was evaluated via coefficient of variation (CV) and intraclass correlation coefficient (ICC).
Nonlinear simulations were completed in an average of 14 minutes per three-dimensional image data set involving analysis of 61 strain levels. The predicted yield strain/strength, ultimate strain/strength, modulus of resilience, and toughness had a mean value of 0.78%, 3.09 MPa, 1.35%, 3.48 MPa, 14.30 kPa, and 32.66 kPa, respectively, covering a substantial range by a factor of up to 4. Intraclass correlation coefficient ranged from 0.986 to 0.994 (average 0.991); CV ranged from 1.01% to 5.62% (average 3.6%), with yield strain and toughness having the lowest and highest CV values, respectively.
The data suggest that the yield and post-yield parameters have adequate reproducibility to evaluate treatment effects in interventional studies within short follow-up periods.
通过系列重现性评估基于高分辨率活体磁共振成像的非线性微有限元模型预测松质骨屈服和屈服后行为的性能。
该非线性模型通过根据组织水平有效应变迭代调整组织水平模量来捕获材料非线性。它通过在台式计算机上通过迭代算法求解一系列非线性系统，从活体分辨率的微磁共振图像模拟松质骨屈服和屈服后行为。在骨质疏松性骨折通常发生的绝经前和绝经后女性（N = 20，年龄范围 50-75 岁）的远端桡骨处估计力学能力（屈服应变/强度、极限应变/强度、回弹模量和韧性）。每位受试者接受了三次扫描（20.2 ± 14.5 天）。通过变异系数（CV）和组内相关系数（ICC）评估序列重现性。
平均每个涉及 61 个应变水平分析的三维图像数据集完成非线性模拟需要 14 分钟。预测的屈服应变/强度、极限应变/强度、回弹模量和韧性的平均值分别为 0.78%、3.09 MPa、1.35%、3.48 MPa、14.30 kPa 和 32.66 kPa，涵盖了高达 4 倍的较大范围。组内相关系数范围为 0.986 至 0.994（平均 0.991）；CV 范围为 1.01%至 5.62%（平均 3.6%），其中屈服应变和韧性的 CV 值最低和最高。
数据表明，屈服和屈服后参数具有足够的重现性，可以在短期随访内评估干预研究中的治疗效果。
