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Title page for ETD etd-08042017-191021

Type of Document Dissertation
Author Conley Griesenauer, Rebekah Helene
URN etd-08042017-191021
Title Development of an Image Guidance System for Breast Cancer Surgery
Degree PhD
Department Biomedical Engineering
Advisory Committee
Advisor Name Title
Michael I. Miga Committee Chair
Benoit Dawant Committee Member
Brett Byram Committee Member
Ingrid M. Meszoely Committee Member
Jared A. Weis Committee Member
  • biomechanical model
  • breast conserving surgery
  • image processing
  • registration
  • finite element method
Date of Defense 2017-05-30
Availability unrestricted
Breast cancer is the most common cancer in women and the second highest cause of cancer related deaths among women in the United States. Most breast cancers are treated by some form of surgical intervention. Breast conservation therapy (BCT) is a desirable option for many women diagnosed with early stage breast cancer and involves a lumpectomy followed by radiotherapy. Unfortunately, the current re-excision rates for breast conserving surgeries due to positive margins average 20-40%. The high re-excision rates arise from difficulty in localizing tumor boundaries intraoperatively and lack of real time information on the presence of residual disease. This thesis addresses the need for improved surgical tools to localize tumors intraoperatively with the ultimate goal of reducing the number of reoperations associated with lumpectomy surgeries. The localization approach developed herein utilizes volumetric images of the breast taken prior to surgery and digitization technology to map patient images to the surgical space. Patient-specific tissue properties and biomechanical models are incorporated to correct the deformation that occurs between the breast geometry acquired by preoperative imaging and the breast geometry observed in the surgical setup. Once the preoperative images are corrected and co-registered to the patient in the operating room, surgeons can effectively navigate to tumors by using the co-registered preoperative images as patient-specific maps. Here, the groundwork for an image guidance system for breast cancer surgery has been laid. This is the first surgical guidance system to incorporate not only patient specific anatomy via high resolution contrast enhanced image volumes, but also patient specific physical parameters through a novel stiffness estimation framework. Building upon this framework will ultimately lead to a superior tumor localization tool for breast cancer surgery and a reduction in the amount of reoperations caused by incomplete tumor removal.

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