Computational Modeling of Scar Formation and Remodeling in Mechanically Loaded Tissues

机械负载组织中疤痕形成和重塑的计算模型

• 批准号: 1332530
• 负责人: Jeffrey Holmes
• 金额: $ 39.5万
• 依托单位: University of Virginia Main Campus
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-09-01 至 2018-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1332530&HistoricalAwards=false
• 关键词: Computational; Modeling; Scar; Formation; Remodeling

The research objective of this award is to develop a computational model that can predict how mechanical loading interacts with other factors to determine scar structure across multiple tissues. A wide range of mechanically loaded tissues including skin, tendon, ligament, and heart respond to injury by forming a collagen-rich scar. The collagen fiber structure of the developing scar is often the single most important determinant of how well the healing tissue continues to function, and evidence suggests that manipulating collagen alignment could improve everything from heart function after myocardial infarction to the strength of surgically repaired tendons. Yet therapies for all of these conditions, from polymer injection into myocardial infarcts to physical therapy routines for tendon injuries, are devised entirely through trial-and-error, because there is no way to predict the long-term effects of proposed interventions on healing tissues. Work under this award will combine agent-based models that simulate fibroblast decisions at the cellular level with finite-element models that represent mechanics at the tissue level to understand, incorporate, and predict the effects of regional heterogeneity, mechanical loading history, and strain-dependent collagen degradation on scar formation in mechanically loaded tissues.Healing and repair of mechanically loaded tissues influences the societal impact of everything from heart attacks to workplace injuries to aging. If successful, these studies could therefore have a broad impact by providing the capability to predict the long-term effects of a wide range of therapeutic interventions in heart, tendon, ligament, and skin, enabling computational design of better treatment strategies. Educational efforts under this proposal aim to excite students at multiple educational levels about studying math, computing, and engineering by introducing them to the power of computational modeling and the role of engineers in integrating the ever-increasing supply of data to understand systems-level behavior and problems.

该奖项的研究目标是开发一种计算模型，可以预测机械负荷如何与其他因素相互作用，以确定多个组织的疤痕结构。各种机械负荷的组织，包括皮肤、肌腱、韧带和心脏，对损伤的反应是形成富含胶原蛋白的疤痕。正在形成的疤痕的胶原纤维结构通常是愈合组织继续发挥功能的唯一最重要的决定因素，有证据表明，操纵胶原排列可以改善从心肌梗死后的心脏功能到手术修复的肌腱的强度等方方面面。然而，所有这些疾病的治疗方法，从心肌梗死聚合物注射到肌腱损伤的物理治疗常规，完全是通过反复试验来设计的，因为没有办法预测拟议的干预措施对愈合组织的长期影响。该奖项的工作将把在细胞水平模拟成纤维细胞决策的基于试剂的模型与在组织水平代表力学的有限元模型相结合，以了解、结合和预测区域异质性、机械负荷历史和应变依赖的胶原降解对机械负荷组织中疤痕形成的影响。机械负荷组织的愈合和修复影响从心脏病发作到工伤到衰老的一切社会影响。因此，如果成功，这些研究可能会产生广泛的影响，因为它们能够预测心脏、肌腱、韧带和皮肤的各种治疗干预的长期效果，从而能够计算出更好的治疗策略。这项提议下的教育努力旨在通过向学生介绍计算建模的力量以及工程师在整合日益增长的数据以了解系统级行为和问题方面的作用，来激发多个教育级别的学生学习数学、计算和工程。