Center for NeuroTrauma Research, Department of Neurosurgery, Medical College of Wisconsin, Milwaukee, WI, USA.
Center for NeuroTrauma Research, Department of Neurosurgery, Medical College of Wisconsin, Milwaukee, WI, USA.
Med Eng Phys. 2022 Sep;107:103857. doi: 10.1016/j.medengphy.2022.103857. Epub 2022 Jul 21.
Finite element models of the head and neck are widely used in automotive and clinical fields to understand spinal biomechanics. These models are developed based on CT and MRI scans of the subjects, but historically the muscle data are obtained from cadaveric specimen. The cadaver data is often obtained from older specimens which commonly have undergone degenerative changes resulting in reduction in muscle cross section area. The objective of the current study is to compare the muscle cross-section area used by various finite element models of neck muscles used in the literature and to develop a normalization technique to scale the MRI muscle cross-section area with those available in the literature. Four male and seven female healthy asymptomatic young adult volunteers enrolled in the study after obtaining necessary approval from Institutional Review Board. T1 and T2 weighted magnetic resonance imaging was performed in neutral upright sitting position wearing military helmet. Muscle cross sectional area was obtained for multifidus muscles from the MRI images. Data was compared with those in the literature. Based on the literature review of prior studies, the cross-sectional area of cadaver specimens was smaller than the MRI obtained muscle area. Multifidus muscle scaling factor was obtained by ratio of sum of MRI cross section area with that of cadaver data. Based on the analysis, the scaling factor for male data is 1.6 and for female data is 1.3. the cadaver data can be multiplied by the scaling factor to obtain the MRI specific cross-sectional area. A Normalization technique was developed for scaling MRI data into finite element model. This technique can be used in developing subject specific finite element model of spine which has applications in clinical, automotive, and military environment.
头部和颈部的有限元模型广泛应用于汽车和临床领域,以了解脊柱生物力学。这些模型是基于对研究对象的 CT 和 MRI 扫描开发的,但历史上肌肉数据是从尸体标本中获得的。尸体数据通常来自于已经发生退行性变化的老年标本,这会导致肌肉横截面积减少。本研究的目的是比较文献中使用的各种颈部肌肉有限元模型的肌肉横截面积,并开发一种标准化技术,将 MRI 肌肉横截面积与文献中可用的肌肉横截面积进行归一化。在获得机构审查委员会的必要批准后,四名男性和七名女性健康无症状的年轻成年志愿者参加了这项研究。志愿者在中立直立坐姿下进行 T1 和 T2 加权磁共振成像,并佩戴军用头盔。从 MRI 图像中获得多裂肌的肌肉横截面积。将数据与文献中的数据进行比较。基于对先前研究的文献回顾,尸体标本的横截面积小于 MRI 获得的肌肉面积。通过将 MRI 横截面积与尸体数据的总和进行比较,获得多裂肌的缩放因子。根据分析,男性数据的缩放因子为 1.6,女性数据的缩放因子为 1.3。可以将尸体数据乘以缩放因子以获得特定于 MRI 的横截面积。开发了一种将 MRI 数据归一化为有限元模型的技术。该技术可用于开发特定于脊柱的有限元模型,在临床、汽车和军事环境中有应用。