Developing a hybrid experimental-computational framework for designing optimized surgical solutions

尽管有几十年的研究，我们仍然不能精确地量化人类膝盖的韧带如何促进关节运动和稳定性。不幸的是，这种知识的缺乏阻碍了了解健康关节生物力学或预测疾病，损伤和修复的影响的努力。使用实验技术，我们不可能重复地移除、重新安装或重新定位韧带，以便参数化地分析它们在关节生物力学中的作用。另一方面，计算模型（易于参数分析）在准确描绘整个关节（包括软骨和半月板）方面存在局限性。 PI的研究计划的长期目标是创建有关关节结构生物力学的基础知识，使用混合实验计算技术实现，该技术协同联合收割机结合实验和计算方法的优势，同时克服各自的弱点。本研究项目的短期（五年）目标是使用参数分析和创新的混合关节测试技术更好地了解韧带如何对正常膝关节生物力学做出贡献，其中真实的膝关节由计算机模拟和完全参数化的虚拟韧带稳定和引导。这些虚拟韧带的运动学、缠绕路径和力贡献将使用并行计算模型在真实的时间中计算，并且被结合回到控制真实的关节的运动的机器人系统中。这种闭环实验计算分析和模拟关节行为，包括虚拟韧带缠绕，从来没有被证明。这一目标将通过完成两个具体目标来实现，首先关注正常膝关节运动期间膝关节韧带力伸长和缠绕行为的表征，然后开发计算机模型，用于在体外生物力学实验期间准确虚拟化膝关节韧带。 这项研究的成果将包括膝关节韧带生物力学的新基础知识，混合关节建模的新技术，以及可应用于膝关节损伤，修复和手术创新研究的新平台。这项研究的成果将影响自然科学和工程研究，重点是增强对所有人类关节生物力学的理解，并将为混合实验计算技术的未来研究奠定基础。这也将对专注于改善膝关节手术患者护理的临床研究产生影响。最后，为参与这项研究的高素质人员提供的跨学科培训机会是完全独特的，HQP开发的技能和专业知识将成为未来行业和学术界职业生涯的宝贵资产。

Despite decades of studies, we still can't quantify precisely how ligaments in human knees contribute to joint motion and stability. Unfortunately, this lack of knowledge hinders efforts to understand healthy joint biomechanics, or predict the effects of disease, injury, and repair. Using experimental techniques, it is impossible for us to repeatedly remove, reinstall, or relocate ligaments in order to parametrically analyze their roles in joint biomechanics. On the other hand, computational models (which readily facilitate parametric analyses) present limitations with respect to an accurate portrayal of the entire joint (including cartilage and meniscus). The long-term goal of the PI's research program is to create fundamental knowledge about the structural biomechanics of joints, achieved using hybrid experimental-computational techniques that synergistically combine the strengths of experimental and computational approaches, while overcoming their individual weaknesses. The short-term (five year) goal of this research program is to better understand how ligaments contribute to normal knee joint biomechanics using parametric analyses with an innovative hybrid joint testing technique where real knee joints are stabilized and guided by computer-simulated and fully parametric virtual ligaments. The kinematics, wrapping paths and force contributions of these virtual ligaments will be computed in real time using a parallel computational model, and incorporated back into a robotic system controlling the motion of the real joint. Such closed-loop experimental-computational analysis and simulation of joint behavior, including virtual ligament wrapping, has never been demonstrated. This goal will be achieved through the completion of two specific aims, first focusing on characterization of knee ligament force-elongation and wrapping behaviors during normal knee motions, and then development of a computer model for accurate virtualization of knee ligaments during in vitro biomechanics experiments. The outcomes of this research will include new fundamental knowledge of knee ligament biomechanics, new techniques for hybrid joint modelling, and a novel platform that can be applied to studies of knee injury, repair, and surgical innovation. The outcomes of this research will impact upon natural science and engineering research focused on an enhanced understanding of the biomechanics of all human joints, and will lay a foundation for future research in hybrid experimental-computational techniques. There will also be an impact upon clinical research focused on improving care of patients undergoing knee surgeries. Finally, the interdisciplinary training opportunities provided to highly qualified personnel involved with this research are entirely unique, and the skills and expertise HQP develop will be valuable assets for future careers in industry and academia.