
Computational Modeling of Skin Behavior and Neo-tissue Formation in Post-Mastectomy Breast Reconstruction with Tissue Expansion
Abstract
Post-mastectomy breast reconstruction using tissue expanders is a widely adopted technique that relies on controlled mechanical stretching of skin and soft tissues to facilitate neo-tissue formation. This study presents a computational modeling framework to simulate skin behavior and tissue growth during the expansion process. Utilizing a finite element approach combined with growth algorithms, the model accounts for the skin’s nonlinear anisotropic properties, mechanical adaptation, and the biological response of surrounding tissues. The simulation results demonstrate key insights into stress distribution, tissue strain patterns, and rates of neo-tissue generation, which closely align with observed clinical outcomes. By validating the model against empirical data, the study offers predictive capabilities for optimizing expander design, placement, and inflation protocols. This computational strategy not only enhances the understanding of tissue mechanics in reconstructive surgery but also supports personalized surgical planning for improved aesthetic and functional results.
Keywords
Computational Modeling, Skin Biomechanics, Tissue Expansion
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