Hoyt, Kenneth2018-03-212018-03-212017-122017-12December 2http://hdl.handle.net/10735.1/5658Cancer is the second leading cause of death, in the United States. An estimate of 255,180 new cases of breast cancer are expected in 2017. The number of deaths due to breast cancer for women are estimated to exceed 40,000 in this same year [1]. National expenditures for cancer care in the United States totaled nearly $125 billion in 2010 and could reach $156 billion in 2020 [2]. As a predominantly age-linked disease, these Figures are expected to rise with increasing population life expectancy. Improvements in noninvasive early cancer detection or monitoring treatment would greatly help in the way therapy is delivered to cancer patients. DCE-US imaging has shown potential in helping oncologists in the management of patients diagnosed with, and treated for, cancer. When exposed to US, intravascular MB contrast agents produce a unique signal compared to the surrounding tissue. These unique signals can be isolated and used to give valuable insight into the tumor angiogenic network helping support cancer growth. Current software packages for analyzing DCE-US images are costly and have limited accessibility to the research community. Thus, there is a growing demand for a more widespread and cost-effective solution to help analyze tumor angiogenic properties. To that end, a custom open-source software solution for processing DCE-US images was developed during this thesis project. This new Matlab-based software can be used to characterize the perfusion properties associated with tumor growth and quantify any changes related to drug treatment response (or lack thereof). We hypothesize that this new image processing tool will develop into an asset in personalized medicine and positively impact cancer management.application/pdfenOpen source softwareContrast-enhanced ultrasoundCancer—PatientsTumors—GrowthThesis2018-03-21