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
这项教师早期职业发展(Career)资助将提高我们对老年人和糖尿病脆性骨骼疲劳骨折的机制起源的理解。这将通过将骨骼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破坏机制,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,尤其是舞者。这些骨折在骨质脆弱的人群中也很常见。例如,老年和糖尿病患者的骨骼胶原蛋白质量差,变得脆弱。断裂通常被认为是单一超载事件的结果,例如坠落。然而,这可能不能解释所有灾难性骨折的原因,因为它忽略了日常活动疲劳的作用。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转移的方法框架,并促进受生物设计原理启发的新型抗断裂材料的开发。该研究将被纳入长期教育计划,通过舞蹈课程和其他创造性学习支持来吸引下一代女性工程师。值得注意的是,与美国其他地区相比,犹他州的女工程专业学生人数尤其不足,这项工作将在犹他州完成。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的机器学习算法的新合成来捕捉机械加载过程中的三维损伤演变,从而推动新的骨折力学理论的发展。先前的研究表明,标准的同步加速器微型计算机断层扫描成像通常无法实现这一目标,因为它涉及高辐射剂量,并导致组织机械性能的恶化。这项研究工作将验证胶原交联积累和其他糖尿病性骨质量变化在脆性骨折中起重要作用的假设。本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的(唯一)影响;(ii)与其他骨质量因素相比,评估胶原交联积累对糖尿病骨抵抗的贡献;(iii)在原位疲劳和断裂试验中,量化糖尿病和富含交联的骨骼变形的微观破坏机制;(iv)评估循环载荷是否可能导致糖尿病和富含交联的骨骼发生骨折的显著比例。该项目可以揭示所有类型胶原组织损伤机制的起源,并具有降低辐射水平和提高医学扫描图像质量的潜力。这一新知识将建立PI在骨折力学方面的长期职业生涯。该奖项反映了美国国家科学基金会的法定使命,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