Date Approved


Graduate Degree Type


Degree Name

Engineering (M.S.E.)

Degree Program

School of Engineering


High morbidity of metastatic tumors in the liver has been observed in several different types of cancers. Liver failure from metastases is one of the primary causes of death in these patients. Effective treatments for liver metastases do not currently exist. However, new pharmaceutical treatments are being explored in a preclinical setting where the cancer and its treatments are designed in vitro and then studied in vivo in mice. Therefore, effective and accurate techniques for non-invasive imaging and analysis of liver metastases in mice are critical to the development of new treatments.

In-vivo micro CT imaging is not only one of the most commonly used imaging technologies in pre-clinical oncology study, but also highly translational. However, it is difficult to apply this technology to studies related to liver metastases due to poor inherent soft tissue contrast and the need for highly technical, manual analysis of the data. The evidence from our research has shown that Kupffer cells (macrophages in the liver) will concentrate among the liver metastases and allow the delivery of macrophage-specific contrast agents for the detection of small metastatic lesions. Using this new contrast enhancement method, CAD software was developed to enable automated detection of liver lesions. Software is able to assess disease stage based on these contrast patterns and compare them over successive weekly scans. The combination of the new imaging and analysis method enables automated detection and evaluation of liver metastases 1 mm or smaller from as early as 1 week. The CAD software allows for better visualization and quantification, but also for large scale longitudinal studies of liver disease and potential treatments. Moreover, it provides new insight into macrophage motility within the liver.