Understanding the Mechanobiological Mechanisms of Soft Tissue Defects and Rupture - Project Summary Soft tissue defects are a prevalent clinical challenge in human health. They may arise from genetic predispositions, trauma, or routine surgical procedures. When these defects fail to heal, they compromise tissue integrity, impair organ function and can progress to chronic illness or rupture. Such rupture events are often catastrophic and remain a major source of morbidity and mortality worldwide. While many genetic, molecular, and cellular factors render the tissue susceptible to damage, it is the subsequent changes in the macroscopic mechanics and the interplay between stress and strength that ultimately dictate whether the defect heals or ruptures. Yet, the mechanobiological mechanisms driving rupture are not fully understood, in part because current methods for studying rupture average properties over the entire specimen and fail to capture the inherently local nature of tissue degeneration, failure, and rupture. This program addresses this gap by advancing an innovative multimodal framework for local mechanobiological assessment of soft tissue defects. Using panoramic digital image correlation, optical coherence tomography, histology, multiphoton imaging, and transcriptomics, we will generate high-resolution, spatially aligned datasets to uncover local structure–function relationships at and around defects. Utilizing the mouse carotid artery, trachea, and stomach as representative soft tissue systems, we will investigate how defect location, geometry, and composition influence rupture thresholds and healing dynamics. In the first experimental project we will study ex vivo-generated defects to test how defect size, location, and composition alter local mechanical properties and rupture potential. In the second experimental project, we will use in vivo models to examine how biologically generated defects remodel under physiological conditions, incorporating analyses of extracellular matrix reorganization, inflammation, and transcriptional signatures. Finally, the resulting data will inform a computational program to model defect initiation, remodeling, and failure. By integrating gradual defect growth through phase-field finite element analysis with rupture events captured by smoothed particle hydrodynamics, these models will allow direct prediction of rupture behavior from experimental data. Together, this integrated approach will provide the first framework to identify key mechanobiological factors that compromise strength and explain why some defects rupture while others heal. Altogether, by applying a framework for local mechanobiological assessment to the complex problem of soft tissue defects, our work will yield critical insights into spatiotemporal rupture prediction and management of defects, ultimately guiding strategies for surgical decision-making, device design, and regenerative therapies.
