Development of Subject Specific Computational Methodology to Study Knee Biomechanics

研究膝关节生物力学的学科特定计算方法的发展

• 批准号: RGPIN-2018-03971
• 负责人: Chandrashekar, Naveen
• 金额: $ 4.66万
• 依托单位: University of Waterloo
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2022
• 资助国家: 加拿大
• 起止时间: 2022-01-01 至 2023-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=760412
• 关键词: Development; Subject; Specific; Computational; Methodology

Osteoarthritis affects about 30 million North Americans and costs around $200 billion per year to treat it. A recent report found that more than 50% of the population affected by knee osteoarthritis are less than 65 years old. Ligament and meniscal injury during athletic activities result in knee osteoarthritis within 10 years of the injury. Since no cure exists for osteoarthritis, prevention of knee injury is the only way to prevent post-traumatic osteoarthritis. However, a clear understanding of the risk factors associated with knee injuries is lacking. Further, there exists no reliable method to assess a specific subject with respect to their knee injury risk. Investigating the external and anatomic risk factors associated with knee injuries is challenging. Deformation in knee tissues cannot be measured through in-vivo methods. In-vitro specimens cannot be loaded multiple times for parametric studies. Creating subject-specific computational models is laborious. An easily implementable methodology to assess knee injury risk in individuals is needed to prevent knee injuries. The goal of this research program is to develop a computational methodology to better understand the knee injury risk factors. The objectives include development and validation of a technique to build subject-specific finite element (FE) model of human knee, which could be used to screen a specific subject for knee injury risk. Further, a validated FE model library will be developed to study the extrinsic and anatomic risk factors associated with knee injury. The program makes use of the unique in-vivo/in-silico/in-vitro method and the unique dynamic knee simulator system pioneered in our lab. A novel mesh-morphing technique will be applied to build 10 distinct FE models of cadaver knees from their MRI scans. The material properties of the tissues will be calibrated to match knee kinematics during experimental loading. These models will be validated using our unique dynamic knee simulator system. This method can then be applied to create individual FE models for live persons. The models will be used to study the effect of individual geometric parameters and tissue properties on knee biomechanics and to build a risk factor model. The proposed research will result in a validated methodology that could be used to screen individuals (ex:aspiring athletes) for knee injury risk. Additionally the library of experimentally validated distinct FE models will be used to perform parametric study on intrinsic/extrinsic factors and to develop knee injury risk factor models. This approach will provide evidence-based outcomes which could potentially lower the incidence of early osteoarthritis, reduce health care costs and increase the quality of life. The research program offers the HQP opportunity to work on unique research techniques in interdisciplinary areas of biomedical engineering.

骨关节炎影响约3000万北美人，每年花费约2000亿美元来治疗它。 最近的一份报告发现，受膝盖骨关节炎影响的人群中有50％的人数小于65岁。运动活动期间的韧带和半月板损伤导致受伤后10年内膝盖骨关节炎。由于没有治愈骨关节炎的治愈方法，因此预防膝盖损伤是预防创伤后骨关节炎的唯一方法。但是，缺乏对与膝盖受伤相关的危险因素的清晰了解。此外，没有可靠的方法来评估特定主题的膝盖伤害风险。 调查与膝关节损伤相关的外部和解剖危险因素是具有挑战性的。膝盖组织的变形不能通过体内方法来测量。体外标本不能多次加载参数研究。创建特定于主题的计算模型很费力。需要一种易于实施的方法来评估个体的膝盖损伤风险，以防止膝盖受伤。 该研究计划的目的是开发一种计算方法，以更好地了解膝关节损伤风险因素。这些目标包括开发和验证人类膝盖的特定主体有限元（FE）模型的技术，该模型可用于筛选特定的膝盖损伤风险。此外，将开发一个经过验证的FE模型库来研究与膝盖损伤相关的外部和解剖风险因素。该程序利用了独特的体内/硅内/体外方法以及在我们实验室中开创的独特动态膝盖模拟器系统。一种新颖的网状技术将应用于通过MRI扫描来建立10种不同的尸体膝盖模型。在实验载荷过程中，将对组织的材料特性进行校准以匹配膝盖运动学。这些模型将使用我们独特的动态膝盖模拟器系统进行验证。然后可以应用此方法来为现场人士创建单个FE模型。这些模型将用于研究单个几何参数和组织特性对膝关节生物力学的影响并建立危险因素模型。拟议的研究将导致经过验证的方法，该方法可用于筛查个人（例如：有抱负的运动员），以实现膝盖伤害风险。此外，经过实验验证的不同FE模型的库将用于对内在/外部因素进行参数研究，并开发膝关节损伤风险因素模型。这种方法将提供基于证据的结果，可能会降低早期骨关节炎的发病率，降低医疗保健成本并提高生活质量。该研究计划提供了HQP的机会，可以在生物医学工程的跨学科领域进行独特的研究技术。