Abstract:
Introduction: Intervertebral Disc (IVD) Degeneration (IDD) is a significant health concern, potentially influenced by mechanotransduction. However, the relationship between the IVD phenotypes and mechanical behavior has not been thoroughly explored in local morphologies where IDD originates. This work unveils the interplays among morphological and mechanical features potentially relevant to IDD through Abaqus UMAT simulations. Methods: A groundbreaking automated method is introduced to transform a calibrated, structured IVD finite element (FE) model into 169 patient-personalized (PP) models through a mesh morphing process. Our approach accurately replicates the real shapes of the patient\'s Annulus Fibrosus (AF) and Nucleus Pulposus (NP) while maintaining the same topology for all models. Using segmented magnetic resonance images from the former project MySpine, 169 models with structured hexahedral meshes were created employing the Bayesian Coherent Point Drift++ technique, generating a unique cohort of PP FE models under the Disc4All initiative. Machine learning methods, including Linear Regression, Support Vector Regression, and eXtreme Gradient Boosting Regression, were used to explore correlations between IVD morphology and mechanics. Results: We achieved PP models with AF and NP similarity scores of 92.06\\% and 92.10\\% compared to the segmented images. The models maintained good quality and integrity of the mesh. The cartilage endplate (CEP) shape was represented at the IVD-vertebra interfaces, ensuring personalized meshes. Validation of the constitutive model against literature data showed a minor relative error of 5.20%. Discussion: Analysis revealed the influential impact of local morphologies on indirect mechanotransduction responses, highlighting the roles of heights, sagittal areas, and volumes. While the maximum principal stress was influenced by morphologies such as heights, the disc\'s ellipticity influenced the minimum principal stress. Results suggest the CEPs are not influenced by their local morphologies but by those of the AF and NP. The generated free-access repository of individual disc characteristics is anticipated to be a valuable resource for the scientific community with a broad application spectrum.
摘要:
简介:椎间盘(IVD)退变(IDD)是一个重要的健康问题,可能受到机械传导的影响。然而,在IDD起源的局部形态中,尚未彻底探索IVD表型与机械行为之间的关系。这项工作揭示了通过AbaqusUMAT模拟可能与IDD相关的形态和机械特征之间的相互作用。方法:引入一种开创性的自动化方法来转换校准,通过网格变形过程将结构化的IVD有限元(FE)模型转换为169个患者个性化(PP)模型。我们的方法准确地复制了患者纤维环(AF)和髓核(NP)的真实形状,同时保持所有模型的拓扑结构相同。使用来自前项目MySpine的分割磁共振图像,使用贝叶斯相干点漂移技术创建了169个具有结构化六面体网格的模型,在Disc4All计划下生成一组独特的PPFE模型。机器学习方法,包括线性回归,支持向量回归,和极限梯度提升回归,用于探索IVD形态与力学之间的相关性。结果:与分割图像相比,我们获得的PP模型的AF和NP相似性得分分别为92.06%和92.10%。模型保持了良好的质量和网格的完整性。软骨终板(CEP)形状在IVD-椎骨界面处表示,确保个性化的网格。根据文献数据验证本构模型的相对误差为5.20%。讨论:分析揭示了局部形态对间接机械传导反应的影响,突出高地的作用,矢状区域,和卷。虽然最大主应力受到高度等形态的影响,圆盘的椭圆率影响最小主应力。结果表明,CEP不受其局部形态的影响,而是受AF和NP的影响。所生成的各个光盘特征的免费访问存储库预计将成为具有广泛应用范围的科学界的宝贵资源。