Erdemir Ahmet, Bennetts Craig, Davis Sean, Reddy Akhil, Sibole Scott
Computational Biomodeling (CoBi) Core , Lerner Research Institute, Cleveland Clinic , Cleveland, OH 44195 , USA ; Department of Biomedical Engineering , Lerner Research Institute, Cleveland Clinic , Cleveland, OH 44195 , USA.
Computational Biomodeling (CoBi) Core , Lerner Research Institute, Cleveland Clinic , Cleveland, OH 44195 , USA ; Department of Biomedical Engineering , Lerner Research Institute, Cleveland Clinic , Cleveland, OH 44195 , USA ; Department of Mechanical Engineering , University of Akron , Akron, OH 44325 , USA.
Interface Focus. 2015 Apr 6;5(2):20140081. doi: 10.1098/rsfs.2014.0081.
Understanding the mechanical environment of articular cartilage and chondrocytes is of the utmost importance in evaluating tissue damage which is often related to failure of the fibre architecture and mechanical injury to the cells. This knowledge also has significant implications for understanding the mechanobiological response in healthy and diseased cartilage and can drive the development of intervention strategies, ranging from the design of tissue-engineered constructs to the establishment of rehabilitation protocols. Spanning multiple spatial scales, a wide range of biomechanical factors dictate this mechanical environment. Computational modelling and simulation provide descriptive and predictive tools to identify multiscale interactions, and can lead towards a greater comprehension of healthy and diseased cartilage function, possibly in an individualized manner. Cartilage and chondrocyte mechanics can be examined in silico, through post-processing or feed-forward approaches. First, joint-tissue level simulations, typically using the finite-element method, solve boundary value problems representing the joint articulation and underlying tissue, which can differentiate the role of compartmental joint loading in cartilage contact mechanics and macroscale cartilage field mechanics. Subsequently, tissue-cell scale simulations, driven by the macroscale cartilage mechanical field information, can predict chondrocyte deformation metrics along with the mechanics of the surrounding pericellular and extracellular matrices. A high-throughput modelling and simulation framework is necessary to develop models representative of regional and population-wide variations in cartilage and chondrocyte anatomy and mechanical properties, and to conduct large-scale analysis accommodating a multitude of loading scenarios. However, realization of such a framework is a daunting task, with technical difficulties hindering the processes of model development, scale coupling, simulation and interpretation of the results. This study aims to summarize various strategies to address the technical challenges of post-processing-based simulations of cartilage and chondrocyte mechanics with the ultimate goal of establishing the foundations of a high-throughput multiscale analysis framework. At the joint-tissue scale, rapid development of regional models of articular contact is possible by automating the process of generating parametric representations of cartilage boundaries and depth-dependent zonal delineation with associated constitutive relationships. At the tissue-cell scale, models descriptive of multicellular and fibrillar architecture of cartilage zones can also be generated in an automated fashion. Through post-processing, scripts can extract biphasic mechanical metrics at a desired point in the cartilage to assign loading and boundary conditions to models at the lower spatial scale of cells. Cell deformation metrics can be extracted from simulation results to provide a simplified description of individual chondrocyte responses. Simulations at the tissue-cell scale can be parallelized owing to the loosely coupled nature of the feed-forward approach. Verification studies illustrated the necessity of a second-order data passing scheme between scales and evaluated the role that the microscale representative volume size plays in appropriately predicting the mechanical response of the chondrocytes. The tools summarized in this study collectively provide a framework for high-throughput exploration of cartilage biomechanics, which includes minimally supervised model generation, and prediction of multiscale biomechanical metrics across a range of spatial scales, from joint regions and cartilage zones, down to that of the chondrocytes.
了解关节软骨和软骨细胞的力学环境对于评估组织损伤至关重要,这种损伤通常与纤维结构的破坏和细胞的机械损伤有关。这一知识对于理解健康和患病软骨中的力学生物学反应也具有重要意义,并且可以推动干预策略的发展,从组织工程构建体的设计到康复方案的制定。跨越多个空间尺度,多种生物力学因素决定了这种力学环境。计算建模和模拟提供了描述性和预测性工具,以识别多尺度相互作用,并可能以个体化方式更深入地理解健康和患病软骨的功能。可以通过后处理或前馈方法在计算机上检查软骨和软骨细胞的力学。首先,关节组织水平的模拟通常使用有限元方法,求解代表关节活动和下层组织的边值问题,这可以区分关节腔室加载在软骨接触力学和宏观软骨场力学中的作用。随后,由宏观软骨力学场信息驱动的组织细胞尺度模拟可以预测软骨细胞变形指标以及周围细胞周和细胞外基质的力学。需要一个高通量建模和模拟框架来开发代表软骨和软骨细胞解剖结构及力学特性的区域和群体差异的模型,并进行适应多种加载情况的大规模分析。然而,实现这样一个框架是一项艰巨的任务,技术难题阻碍了模型开发、尺度耦合、模拟和结果解释的过程。本研究旨在总结各种策略,以应对基于后处理的软骨和软骨细胞力学模拟的技术挑战,最终目标是建立高通量多尺度分析框架的基础。在关节组织尺度上,通过自动生成软骨边界的参数表示和具有相关本构关系的深度依赖性区域划分过程,可以快速开发关节接触的区域模型。在组织细胞尺度上,也可以以自动化方式生成描述软骨区域多细胞和纤维结构的模型。通过后处理,脚本可以在软骨中所需点提取双相力学指标,以便为较低细胞空间尺度的模型分配加载和边界条件。可以从模拟结果中提取细胞变形指标,以提供单个软骨细胞反应的简化描述。由于前馈方法的松散耦合性质,组织细胞尺度的模拟可以并行化。验证研究说明了尺度之间二阶数据传递方案的必要性,并评估了微观尺度代表性体积大小在适当预测软骨细胞力学反应中所起的作用。本研究总结的工具共同提供了一个用于高通量探索软骨生物力学的框架,该框架包括最少监督的模型生成,以及预测从关节区域和软骨区域到软骨细胞的一系列空间尺度上的多尺度生物力学指标。