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

Parent Grant：多尺度建模以预测皮肤的长期生长和重塑 拉伸(1R01AR074525-01A1) 摘要：乳腺癌影响女性一生中的1/8，是全世界第二常见的癌症。 女人。组织扩张术是乳房切除术后最常用的乳房重建技术。 不幸的是，对于大系列的乳房重建，TE的并发症发生率可能是15%或更高， 不包括糟糕的美容和对身体形象的负面影响。在形状和数量上不断增长的皮肤 达到自然的乳房形状是一项关键需求，因为成功的乳房重建已被证明 显著改善幸存者？生活质量。TE在具有复杂三维(3D)的领域具有挑战性 几何图形，它显示了目前无法预测的不均匀拉伸和增长分布。我们有 率先将有限元工具应用于TE，以及在猪身上的一种新的实验方案 这使得我们能够第一次测量组织规模预应变，扩张引起的变形， 并导致现实TE协议的增长。猪的模型证实了我们的预测 计算模型，即变形是不均匀的，膨胀机的顶端经历了 最大的应变，生长模式反映了变形轮廓。在这里，我们将利用我们独特的 动物模型能准确测量组织鳞片的变形和生长，并与之相对应 栓塞术中特定时间点的细胞行为和微结构重塑。此信息将提供 第一张完整的照片，显示了皮肤对不同尺度机械信号的长期适应。这些数据将使我们能够 改进我们以前的计算模型，并创建、校准和验证新的多尺度模型。 具体地说，我们将预测微观重塑作为细胞对拉伸(AIM)反应的行为的函数 1)，使用新的器官尺度模型(目标2)预测组织扩张过程中的皮肤生长，并将 乳腺癌术后再造乳房临床设置预测生长发育的实验和模型 人体皮肤作为充气时机和充气量的函数(目标3)。因此，这个项目将增加基本的 皮肤生物学知识，有助于改善临床结果，并为进一步研究 治疗性干预。

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.