Hollis L, Barnhill E, Perrins M, Kennedy P, Conlisk N, Brown C, Hoskins P R, Pankaj P, Roberts N
University of Edinburgh, Clinical Research Imaging Centre, 47 Little France Crescent, Edinburgh EH16 4TJ, United Kingdom.
Charité Universitatsmedizin Berlin, Charitéplatz 1, 10117 Berlin, Germany.
Magn Reson Imaging. 2017 Nov;43:27-36. doi: 10.1016/j.mri.2017.06.008. Epub 2017 Jun 29.
To develop finite element analysis (FEA) of magnetic resonance elastography (MRE) in the human thigh and investigate inter-individual variability of measurement of muscle mechanical properties.
Segmentation was performed on MRI datasets of the human thigh from 5 individuals and FEA models consisting of 12 muscles and surrounding tissue created. The same material properties were applied to each tissue type and a previously developed transient FEA method of simulating MRE using Abaqus was performed at 4 frequencies. Synthetic noise was applied to the simulated data at various levels before inversion was performed using the Elastography Software Pipeline. Maps of material properties were created and visually assessed to determine key features. The coefficient of variation (CoV) was used to assess the variability of measurements in each individual muscle and in the groups of muscles across the subjects. Mean measurements for the set of muscles were ranked in size order and compared with the expected ranking.
At noise levels of 2% the CoV in measurements of |G| ranged from 5.3 to 21.9% and from 7.1 to 36.1% for measurements of ϕ in the individual muscles. A positive correlation (R value 0.80) was attained when the expected and measured |G| ranking were compared, whilst a negative correlation (R value 0.43) was found for ϕ.
Created elastograms demonstrated good definition of muscle structure and were robust to noise. Variability of measurements across the 5 subjects was dramatically lower for |G| than it was for ϕ. This large variability in ϕ measurements was attributed to artefacts.
开发人体大腿磁共振弹性成像（MRE）的有限元分析（FEA），并研究肌肉力学性能测量的个体间差异。
对5名个体的人体大腿MRI数据集进行分割，并创建由12块肌肉和周围组织组成的FEA模型。将相同的材料属性应用于每种组织类型，并使用Abaqus在4个频率下执行先前开发的模拟MRE的瞬态FEA方法。在使用弹性成像软件管道进行反演之前，将合成噪声以不同水平应用于模拟数据。创建材料属性图并进行视觉评估以确定关键特征。变异系数（CoV）用于评估每个个体肌肉以及受试者群体中肌肉组测量的变异性。将一组肌肉的平均测量值按大小顺序排列，并与预期排名进行比较。
在2%的噪声水平下，单个肌肉中|G|测量的CoV范围为5.3%至21.9%，ϕ测量的CoV范围为7.1%至36.1%。比较预期和测量的|G|排名时获得正相关（R值0.80），而对于ϕ则发现负相关（R值0.43）。
创建的弹性图显示出良好的肌肉结构清晰度，并且对噪声具有鲁棒性。|G|测量值在5名受试者之间的变异性明显低于ϕ。ϕ测量中的这种大变异性归因于伪影。
