Department of Technical Physics, University of Eastern Finland, POB 1627, 70211, Kuopio, Finland.
Diagnostic Imaging Center, Kuopio University Hospital, Kuopio, Finland.
Ann Biomed Eng. 2024 Sep;52(9):2584-2595. doi: 10.1007/s10439-024-03552-7. Epub 2024 Jul 16.
The ability of articular cartilage to withstand significant mechanical stresses during activities, such as walking or running, relies on its distinctive structure. Integrating detailed tissue properties into subject-specific biomechanical models is challenging due to the complexity of analyzing these characteristics. This limitation compromises the accuracy of models in replicating cartilage function and impacts predictive capabilities. To address this, methods revealing cartilage function at the constituent-specific level are essential. In this study, we demonstrated that computational modeling derived individual constituent-specific biomechanical properties could be predicted by a novel nanoparticle contrast-enhanced computer tomography (CECT) method. We imaged articular cartilage samples collected from the equine stifle joint (n = 60) using contrast-enhanced micro-computed tomography (µCECT) to determine contrast agents' intake within the samples, and compared those to cartilage functional properties, derived from a fibril-reinforced poroelastic finite element model. Two distinct imaging techniques were investigated: conventional energy-integrating µCECT employing a cationic tantalum oxide nanoparticle (TaO-cNP) contrast agent and novel photon-counting µCECT utilizing a dual-contrast agent, comprising TaO-cNP and neutral iodixanol. The results demonstrate the capacity to evaluate fibrillar and non-fibrillar functionality of cartilage, along with permeability-affected fluid flow in cartilage. This finding indicates the feasibility of incorporating these specific functional properties into biomechanical computational models, holding potential for personalized approaches to cartilage diagnostics and treatment.
关节软骨在行走或跑步等活动中能够承受较大的机械应力,这依赖于其独特的结构。由于分析这些特性的复杂性,将详细的组织特性整合到特定于主体的生物力学模型中具有挑战性。这一限制降低了模型复制软骨功能的准确性,并影响了预测能力。为了解决这个问题,揭示软骨在特定于成分水平上的功能的方法至关重要。在这项研究中,我们证明了一种新的纳米颗粒对比增强计算机断层扫描(CECT)方法可以预测计算建模得出的个体特定于成分的生物力学特性。我们使用对比增强微计算机断层扫描(µCECT)对来自马膝关节的关节软骨样本进行成像,以确定样本中对比剂的摄取量,并将其与源自纤维增强多孔弹性有限元模型的软骨功能特性进行比较。我们研究了两种不同的成像技术:采用阳离子氧化钽纳米颗粒(TaO-cNP)对比剂的常规能量积分µCECT 和利用包含 TaO-cNP 和中性碘克沙醇的双重对比剂的新型光子计数µCECT。结果表明,该方法能够评估软骨的纤维状和非纤维状功能以及受渗透性影响的软骨内流体流动。这一发现表明,将这些特定的功能特性纳入生物力学计算模型是可行的,这为个性化的软骨诊断和治疗方法提供了潜力。