Computational framework for local breast cancer treatment.
详细信息
文摘
Breast cancer is the most common cancer among women in the developed as well as the developing countries. There are a plethora of proposed solutions regarding possible medical interventions for breast cancer---one in particular is Breast Conserving Therapy BCT). BCT comprises of complete surgical excision of the tumor partial mastectomy),and post-operative radiotherapy for the remaining breast tissue. This is a feasible treatment for most women with breast cancer. The goal of BCT is to achieve local control of the cancer,as well as to preserve breast shape that appeases a womans cosmetic concerns. Although these goals are usually achieved,there are still occasional unexpected results,such as reexcision of the tumor due to a positive margin assessment,tumor local recurrence,unsatisfactory cosmetic results,and breast pain. Other than surgical experience and judgment,there are currently no tools which can predict the outcome of partial mastectomy on the contour and deformity of the treated breast. The objective of this dissertation is to propose computational framework,which contributes to BCT operations,this was achieve by exploring two areas. On the one hand we developed a multiscale model adapted for breast cancer tumor growth,ductal carcinoma in situ DCIS). The model features included: nutrients growth limitation,wall degradation enzyme and HER2 chemical expression tumor phenotype. Our model successfully simulate some pattern of DCIS carcinoma. Among the interesting result we showed that the enzyme contributed to a greater tumor size and that when HER2 was overexpressed,the growth limiting factor was the EGFR. On the other hand,we developed a virtual surgery box to simulate BCT surgery. The box will input MRI patient data and will output cosmetic and functional indicator to rate the impact of the surgery. It appears that stiffness of the tissue,resection radius as well as the lump quadrant location are the most sensitive parameters to the indicators. A healing model was also embedded to simulate the wound closure after resection,this model was stress dependent and illustrate an asymmetric wound closure progression. The tools developed in this research allows a new type of field convergence between the surgery and computation field. At the local level it will allow surgeons and patient to be able to communicate on the pertinence and necessity of performing a lumpectomy surgery,enabling to anticipate the possible outcome of the operation. On the global aspect this type of tool gives birth to a new type of field: computational surgery,where computer scientist and surgeons work hand in hand to provide the best and the most reliable service to the patients.