Events

Past Event

Seminar: Digital Twins of Skin & Breast Tissue Biomechanics

February 7, 2025
12:00 PM - 1:00 PM
America/New_York
Mudd Hall, 500 W. 120 St., New York, NY 10027

Title: Digital Twins of Skin & Breast Tissue Biomechanics and Mechanobiology

Guest Speaker: Dr. Adrian Buganza-Tepole, Associate Professor of Mechanical Engineering at Purdue University

Moderator: Dr. Kristin Myers, Associate Professor of Mechanical Engineering at Columbia University

Description: This talk focuses on our recent efforts to develop mechanistic models and leverage machine learning (ML) and data-driven approaches to increase our fundamental understanding of soft tissue, its unique ability to adapt to mechanical cues, and to create personalized treatment strategies based on digital twin frameworks. We explore two complex phenomena, breast wound healing and skin growth in tissue expansion, which are central to the successful reconstruction of the breast following breast cancer treatment. Breast cancer is the most common cancer in women and affects approximately one in eight women over their lifetime. The standard-of-care surgical methods for breast cancer treatment are lumpectomy (or breast-conversing surgery) and mastectomy (or total breast removal). Lumpectomy leads to wound healing which can cause significant breast deformity, while mastectomy requires breast reconstruction, often based on tissue expansion. For the first part of the talk, focused on wound healing, the emphasis is on new numerical methods and analysis tools to couple changes in tissue mechanics to dynamical regulatory systems of cell and cell-cell interactions. The second part of the talk tackles skin growth in tissue expansion, a technique that grows new skin in response to sustained supra-physiological loading. We have created computational models that combine mechanics and mechanobiology to describe the deformation and growth of expanded skin. Together with experiments on a porcine model, and leveraging ML tools such as multi-fidelity Gaussian processes, we have performed Bayesian inference to learn mechanistically how skin grows in response to stretch. These models, together with the experimental data they are built on, are key for the improvement of reconstructive procedures in breast cancer survivors, a substantial burden to the US healthcare system and globally.

Contact Information

Kyoko Thompson