Finite Element Analysis of Breast Implants

• Main Author: Wilson, Kelly A.
• Other Authors: Engineering Mechanics
• Format: Others
• Published: Virginia Tech 2014
• Subjects: breast implants; finite element model
• Online Access: http://hdl.handle.net/10919/32972; http://scholar.lib.vt.edu/theses/available/etd-051899-161726/

The Breast Implant Lifetime Study at Virginia Tech, on which this thesis is based, seeks to develop methods and data for predicting the lifetime of saline-filled implants. This research developed Finite Element Analysis (FEA) models to evaluate the stresses that are present in the silicone breast implant material under different loading situations. The FEA work was completed using the commercial codes PATRAN and ABAQUS. PATRAN was used for pre- and post-processing, while ABAQUS was used for the actual analysis and to add fluid and contact elements not supported by PATRAN. Many different loading situations and constraints were applied to these models, as well as variations in the material and model properties. Varying the Poisson's ratio of the implant material from 0.45 to 0.49 did not make a significant difference in the results. Changing the elastic modulus of the implant material from the modulus of a Smooth implant to the modulus of a Siltex implant had a noticeable effect on the stress results, increasing the maximum stresses by almost 8%. Changing the modulus of the surrounding tissue had marked effects as well, with stiffer tissue (E=300 psi) decreasing the implant's stresses by about 60% as compared to softer tissue (E=100 psi). A ten percent decrease in implant thickness yielded a 17% average increase in stress experienced by the implant. For both the 2.5" radius and the 4" radius tissue models, using CAX4 elements produced higher overall stresses in the tissue with the same loading conditions. However, in the 2.5" tissue model, the implant itself experienced less stress with the CAX4 tissue than the CAX3 tissue. In the 4" tissue model, the implant experienced more stress when surrounded by the CAX4 tissue elements. These models will be combined with implant fatigue data to develop a life prediction method for the implant membrane. === Master of Science