Multi-Scale Modeling to Predict Long-Term Growth and Remodeling of Skin in Response to Stretch

父母资助：多尺度模型预测皮肤的长期生长和重塑

Parent grant: Multi-Scale Modeling to Predict Long-Term Growth and Remodeling of Skin in Response to Stretch (1R01AR074525-01A1) Abstract: Breast cancer affects 1 in 8 women over their lifetime, and is the second most common cancer in women. Tissue expansion (TE) is the most common technique for breast reconstruction after mastectomy. Unfortunately, the rate of complications with TE for breast reconstruction can be 15% or higher in large series, not including poor cosmetic and the negative impact to body image. Growing skin in shape and amount adequate to achieve a natural breast shape is a key need, as successful reconstruction has been shown to markedly improve survivors? quality of life. TE is challenging in areas with complex three-dimensional (3D) geometries, which show unequal stretch and growth distributions that cannot be currently anticipated. We have pioneered the application of finite element tools to TE, as well as a novel experimental protocol in the swine that has allowed us to measure, for the first time, tissue scale prestrain, deformation induced by expansion, and resulting growth in realistic TE protocols. The porcine model has confirmed predictions made with our computational model, that the deformation is heterogeneous, with the apex of the expander undergoing the largest strains, and that the growth patterns reflect the deformation contours. Here we will leverage our unique animal model to measure accurately the tissue scale deformation and growth, together with the corresponding cell behavior and microstructure remodeling at specific time points during TE. This information will provide the first complete picture of chronic skin adaptation to mechanical cues across scales. The data will allow us to improve our previous computational model, and create, calibrate and validate a new multi-scale model. Specifically, we will predict microscopic remodeling as a function of cell behavior in response to stretch (Aim 1), predict skin growth during tissue expansion using a new organ-scale model (Aim 2), and translate the experiment and model to the clinical setting of breast reconstruction after mastectomy to predict the growth of human skin as a function of inflation timing and volume (Aim 3). This project will thus add to the fundamental knowledge of skin biology, help improve clinical outcomes and provide topics for further research into therapeutic intervention.