title: Interrogating a multifactorial model of breast conserving therapy with clinical data.
abstract: Most women with early stage breast cancer do not require removal of the entire breast to treat their cancer; instead, up to 70% of women can be effectively and safely treated by breast conserving therapy (BCT) with surgical removal of the tumor only (lumpectomy) followed by radiation treatment of the remaining breast tissue. Unfortunately, the final contour and cosmesis of the treated breast is suboptimal in approximately 30% of patients. The ability to accurately predict breast contour after BCT for breast cancer could significantly improve patient decision-making regarding the choice of surgery for breast cancer. Our overall hypothesis is that the complex interplay among mechanical forces due to gravity, breast tissue constitutive law distribution, inflammation induced by radiotherapy and internal stress generated by the healing process play a dominant role in determining the success or failure of lumpectomy in preserving the breast contour and cosmesis. We have shown here from a first patient study that even in the idealistic situation of excellent cosmetic outcome this problem requires multiscale modeling. We propose a method to decide which component of the model works best for each phase of healing and what parameters should be considered dominant and patient specific. This patient study is part of a clinical trial registered on ClinicalTrial.gov, identifier NCT02310711.
authors.affiliation: Department of Computer Science, University of Houston, Houston, TX, USA.
authors.forename: Remi
authors.initials: R
authors.lastname: Salmon
authors.affiliation: Department of Biology and Biochemistry, University of Houston, Houston, TX, USA; Methodist Institute for Technology, Innovation and Education, Houston, TX, USA.
authors.forename: Marc
authors.initials: M
authors.lastname: Garbey
authors.affiliation: Department of Surgery, Houston Methodist, Houston, TX, USA.
authors.forename: Linda W
authors.initials: LW
authors.lastname: Moore
authors.affiliation: Methodist Institute for Technology, Innovation and Education, Houston, TX, USA; Department of Surgery, Houston Methodist, Houston, TX, USA.
authors.forename: Barbara L
authors.initials: BL
authors.lastname: Bass
mesh_terms: D001943:Breast Neoplasms / Q000473:pathology* / Q000601:surgery; D000066491:Clinical Decision-Making; D005260:Female; D006801:Humans; D008279:Magnetic Resonance Imaging; D015412:Mastectomy, Segmental / Q000379:methods; D008875:Middle Aged; D066230:Patient-Specific Modeling