Determining Nipple Position and Smallest Resolvable Volume for Evaluating Breast Reconstruction Surgery

Breast cancer is one of the most widespread cancers among women globally. Because of recent improvements in cancer treatment and increase in survival rate, more women are living with the consequences of breast removal surgery, known as mastectomy. In order to improve the quality of life, physical and psychological well-being after the cancer treatment process, many women decide to have reconstruction surgery. Metrics of breast aesthetics such as position and volume symmetry are often used for outcome assessment following reconstructive surgery. In order to achieve breast symmetry, many measurements which are difficult for human eyes to precisely estimate need to be done. The first aim of this study is to use a data-driven approach to help surgeons annotate the nipple position on reconstructed breast mounds. A graphical user interface was developed to enable computations of nipple localization and symmetry measurements on 3D surface images of pre- and post-operative patients, and a linear regression model incorporating breast aesthetic measures was developed to provide personalized estimate of nipple localization. Secondly, the smallest measurable volume using 3D imaging was analyzed to quantify the resolution of the 3D imaging system. The computational tools and models developed in this study will assist surgeons with surgical planning and outcome assessment and provide a framework for visualization to support physician-patient communication during clinical consultations. This research aims to benefit breast cancer survivors as well as their care givers.Engineering Technology, Department o