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

项目摘要 乳腺癌影响女性一生中的1/8，是女性中第二常见的癌症。组织 乳房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的并发症发生率可达15%或更高，不包括差的 化妆品和对身体形象的负面影响。在形状和数量上生长的皮肤足以达到 自然的乳房形状是一个关键需求，因为成功的乳房重建被证明显著改善了幸存者的 生活质量。TE在具有复杂的三维(3D)几何图形的区域中具有挑战性，这些区域显示出不相等 目前无法预测的伸展和增长分布。我们开创了有限元应用的先河 元素工具，以及一种在猪身上的新实验方案，使我们能够测量 第一次，组织尺度预应变，由膨胀引起的变形，并导致在真实的TE中生长 协议。猪的模型证实了我们的计算模型所做的预测，即 变形是不均匀的，膨胀机的顶端经历了最大的应变，生长 图案反映了变形轮廓。在这里，我们将利用我们独特的动物模型来精确测量 组织尺度的变形和生长，以及相应的细胞行为和微观结构 经皮冠状动脉介入治疗中特定时间点的重塑。这一信息将提供慢性病的第一幅完整图景 皮肤对不同尺度的机械暗示的适应。这些数据将使我们能够改进之前的计算 建立模型，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 作为拉伸反应中细胞行为的函数的重塑(目标1)，预测组织中的皮肤生长 使用新的器官比例模型(目标2)进行扩展，并将实验和模型转化为临床环境 乳房切除术后乳房重建预测皮肤生长与充气时机的关系 和音量(目标3)。该项目将因此增加皮肤生物学的基础知识，帮助改善临床 结果，并为进一步研究治疗干预提供主题。

Project Summary 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.