Computational modeling of breast conserving surgery (bcs) starting from MRI imaging
Document Type
Journal Article
Publication Date
1-1-2014
Journal
Computational Surgery and Dual Training: Computing, Robotics and Imaging
DOI
10.1007/978-1-4614-8648-0_5
Keywords
Breast cancer; Breast conservative therapy; Cosmetic outcome; Image segmentation; Lumpectomy; Magnetic resonance imaging; Mechanical stress; Quality of life; Soft tissue mechanic; Tissue stiffness; Tumor
Abstract
© Springer Science+Business Media New York 2014. Breast conserving therapy (BCT) is a less radical surgery consisting of the removal of the tumor (partial mastectomy) including a negative margin followed by radiotherapy. It provides the same incidence of local recurrence—reappearance of the cancer in the vicinity of a previously removed cancer—than a complete mastectomy (complete removal of the breast), with the advantage of offering faster recovery and better cosmetic outcome for patients. Nevertheless, many patients remain with some major cosmetic defects such as concave deformities, distortion of the nipple aerolar complex, and asymmetric changes.There are currently no procedures, other than surgical experience and judgment, allowing prediction on the impact of partial mastectomy on the contour and the deformity of the treated breast.The present work defines the basic principles of a virtual surgery toolbox that will allow to predict BCT intervention outcome.
APA Citation
Thanoon, D., Garbey, M., & Bass, B. (2014). Computational modeling of breast conserving surgery (bcs) starting from MRI imaging. Computational Surgery and Dual Training: Computing, Robotics and Imaging, (). http://dx.doi.org/10.1007/978-1-4614-8648-0_5