BME (ROBO) Ph.D. Defense Presentation

Date: Thursday, June 7, 2019

Time: 3 -5 pm
Location: Room 1212, Klaus Advanced Computing Building, Georgia Tech Campus

Committee Members: 
Dr. Jaydev P. Desai (Advisor) - Department of Biomedical Engineering, GT
Dr. Jun Ueda - School of Mechanical Engineering, GT
Dr. Frank L. Hammond III - Department of Biomedical Engineering, GT
Dr. Peter J. Hesketh - School of Mechanical Engineering, GT
Dr. David J. Foran – Department of Pathology and Laboratory Medicine, Rutgers University

Title: Micro-scale Characterization of Breast Cancer Using MEMS and Robotics

Abstract: 
According to the cancer statistics from the American Cancer Society, breast cancer is the most common type of cancer in females and continues to be the second leading cause of cancer-related female deaths in the US. As breast cancer progresses, the microenvironment around cancerous breast tissues undergoes a physical reconfiguration to be tumor-permissive. The capability to monitor the signatures of cancer progression in breast tissue is important for improving the accuracy of diagnosis and early detection, which is critical factors for successful treatment and recovery of the patient. The goal of this project is to develop experimental and computational tools to characterize the onset and progression of cancer in human breast tissue at the micro-scale as additional diagnostic methods. More specifically, the dissertation consists of the following three research areas:

1) design, development, and control of micro-manipulators capable of ex vivo tissue indentation, 2) design and fabrication of micro-electromechanical system (MEMS) based sensors, which are a subsystem of the indentation system, for measuring various physical properties of human breast tissues, and 3) analysis and validation of the properties as biomarkers for breast cancer. The ex vivo experimental results show that the proposed system can capture various physical properties of human breast tissues reliably and distinguish cancerous tissues from normal breast tissues. Development of a system for in situ breast tissue characterization as a proof-of-concept is also included to provide a more practical way of breast cancer diagnosis.