CAREER: Discovering the Mechanisms Governing Fracture in Fragile Bones
CAREER: Discovering the Mechanisms Governing Fracture in Fragile Bones
批准号:
2045363
负责人:
Claire Acevedo
金额:
$56.15万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2021
资助国家:
美国
项目状态:
未结题
起止时间:
2021-04-01 至 2026-03-31
中文摘要
这个教师早期职业发展(CAREER)补助金将提高我们对老年人和糖尿病脆弱骨骼疲劳骨折的机械起源的理解。 这将通过将骨损伤的低辐射图像与骨骼的机械测试和机器学习相结合来实现。 这一点很重要,因为疲劳(循环)断裂是几乎所有工程结构中普遍存在的失效机制,但其与骨组织领域的相关性一直被忽视。这些疲劳性骨折在年轻运动员中很常见,尤其是在舞蹈演员中。这些骨折在骨脆弱的人中也很常见。 例如,老年人和糖尿病患者的骨骼胶原蛋白质量差,变得脆弱。 骨折通常被认为是单一过载事件的结果,例如跌倒。然而,这可能无法解释所有灾难性骨折的原因,因为它忽略了日常活动中疲劳的作用。 该研究项目将开发新的动态成像和机器学习,以捕获骨衰竭机制和相关风险因素的起源。研究结果最终将用于预防脆性骨折。这项研究将为医学成像提供一个可移植的方法框架,并促进受生物设计原理启发的新型耐腐蚀材料的开发。这项研究将被纳入一项长期教育计划,通过舞蹈课和其他创造性学习支持吸引下一代女工程师。 值得注意的是,与美国其他地区相比,犹他州的女性工程专业学生人数特别少,因为这项工作将在犹他州进行。该研究的具体目标是通过使用同步辐射微计算机断层扫描和特定机器学习算法的新合成来捕获机械加载过程中的3D损伤演化,从而推进新的骨折力学理论的发展。以前的工作表明,这通常是无法实现的标准同步加速器微计算机断层扫描成像,这涉及高辐射剂量,并导致组织的机械性能的恶化。这项研究工作将验证胶原交联积累和其他糖尿病骨质量变化在驱动脆性骨折中发挥重要作用的假设。该项目的研究任务包括:(i)确定胶原交联积累对疲劳和抗断裂性的(唯一)影响;(ii)评价胶原交联积累与其他骨质量因素相比在糖尿病骨抵抗力中的贡献;(iii)量化原位疲劳和断裂试验期间糖尿病和富含交联的骨变形的微观失效机制;(iv)确定胶原交联积累对疲劳和抗断裂性的(唯一)影响。以及(iv)评估循环载荷是否可能在糖尿病和富含交联的骨中驱动显著比例的骨折。该项目可以揭示所有类型的胶原组织中损伤机制的起源,并有可能降低辐射水平和提高医学扫描的图像质量。这一新知识将建立PI在骨折力学方面的长期职业生涯。该奖项反映了NSF的法定使命,并通过使用基金会的知识价值和更广泛的影响审查标准进行评估,被认为值得支持。
英文摘要
This Faculty Early Career Development (CAREER) grant will improve our understanding of the mechanistic origins of fatigue fracture in aged and diabetic fragile bones. This will be achieved by combining low-radiation images of bone damage with mechanical testing of bones and machine learning. This is important because fatigue (cyclic) fracture is a prevalent failure mechanism in nearly all engineered structures, but its relevance to the field of bone tissues has been neglected. These fatigue fractures are common in young athletes, especially in dancers. These fractures are also common in those who have bone fragility. For example, aged and diabetic bones have poor collagen quality and become fragile. Fractures are often thought to be the result of a single overload event, such as a fall. However, this may not explain the cause of all catastrophic fractures because it overlooks the role of fatigue from daily activities. This research project will develop novel dynamic imaging and machine learning for capturing the origins of bone failure mechanisms and associated risk factors. The results will ultimately be used to prevent fragility fractures. This research will provide a transferrable methodological framework for medical imaging, and foster the development of new fracture-resistant materials inspired by biological design principles. The research will be integrated into a long-term educational plan to attract the next generation of female engineers through dance class and other creative learning supports. It is of note that female engineering students in Utah, where this work will be done, are particularly underrepresented in comparison to the rest of the United States. The specific goal of the research is to advance the development of new bone fracture mechanics theory by using a novel synthesis of synchrotron radiation micro-computed tomography and specific machine learning algorithms to capture the 3D damage evolution during mechanical loading. Previous work has shown that this is typically not achievable by standard synchrotron micro-computed tomography imaging, which involves high radiation doses and causes deterioration of tissue’s mechanical properties. The research work will test the hypothesis that collagen cross-linking accumulation and other diabetic changes in bone quality play an important role in driving fragility fractures. The research tasks of this project include: (i) determine the (sole) effect of collagen cross-linking accumulation on fatigue and fracture resistance ; (ii) evaluate the contribution of collagen cross-linking accumulation in diabetic bone resistance compared with other bone quality factors; (iii) quantify the microscale failure mechanisms in deforming diabetic and crosslinking-rich bones during in situ fatigue and fracture tests; and (iv) evaluate whether cyclic loadings might drive a significant fraction of fractures in diabetic and crosslinking-rich bones. This project can reveal the origins of damage mechanisms in all types of collagenous tissues, and has the potential to lower the radiation level and improve image quality of medical scans. This new knowledge will establish the PI’s long-term career in bone fracture mechanics.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
期刊论文(1)
专著(0)
科研奖励(0)
会议论文
Unraveling the effect of collagen damage on bone fracture using in situ synchrotron microtomography with deep learning
利用深度学习的原位同步加速器显微断层扫描揭示胶原蛋白损伤对骨折的影响
DOI:
10.1038/s43246-022-00296-6
发表时间:
2022
期刊:
Communications Materials
影响因子:
7.8
作者:
[Sieverts, Michael, Obata, Yoshihiro, Rosenberg, James L., Woolley, William, Parkinson, Dilworth Y., Barnard, Harold S., Pelt, Daniël M., Acevedo, Claire]
通讯作者:
Acevedo, Claire
海外基金