LAUSR

The early detection rate of breast cancer and its relative survival rate are persistently increasing, thanks to an active approach to breast cancer exams and enhancement of clinical treatment capabilities. In this new environment, quality-of-life breast reconstructive surgery for those who have undergone a mastectomy for breast cancer treatment has become ever-more attractive. However, there is a problem that occurs, where post-reconstruction breast shapes differ from those before mastectomy. This is caused by insufficient geometric information for the breasts to be reconstructed. Therefore, patients not only go on to suffer inconvenience in daily life, but they also experience a loss of psychological self-esteem owing to an asymmetrical body. In this study, we generate three-dimensional (3D) breast shapes by extracting geometric information from fat and fibro-glandular breast tissues from a series of magnetic resonance imaging images, which are acquired during pre-mastectomy examinations. We then apply a Neo-Hookean material model, which is a hyper-elastic material property model being considered for natural breast-shape deformability. We then use finite element analysis to model the 3D breast by accounting for its deformation characteristics, finally proposing a method to transform the model breast into a shape indicative of a natural, standing posture.