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.
