Breast cancer is the second leading cause of cancer-related deaths in women in the United States. While mammography is the current first line imaging approach, its diagnostic accuracy is very limited in women with dense breast tissue. In those patients, ultrasound is used to supplement mammography for improved breast cancer detection and characterization. However, it often results in false positive findings with multiple unnecessary callbacks, biopsies, associated health care cost, and psychological stress for women. Ultrasound molecular imaging using contrast agents targeted at cancer-associated molecular signatures on the tumor neovasculature, such as kinase domain receptor (KDR), is an emerging strategy that has shown promising results for breast cancer detection and characterization in preclinical animal models as well as in a recent pilot clinical trial performed by our group. However, current limitations include its operator-dependency, limited anatomical coverage, and the lack of an optimized clinical imaging system for wide-spread breast ultrasound molecular imaging. The purpose of this interdisciplinary, academic-industrial collaboration between Stanford University and Siemens Medical Solutions USA, Inc. is to develop, optimize, and clinically test a new operator- independent whole-breast ultrasound imaging system based on a commercially available and widely used automated human breast volume scanner (ABVS), supporting molecular imaging for improved breast cancer imaging in the clinic. We will also develop imaging strategies to mitigate common artifacts encountered in ultrasound molecular imaging of the breast, including spurious contrast signal from tissue signal leakage and acoustic shadowing from the nipple. To assess feasibility and efficacy in the clinic, the new volumetric ultrasound molecular imaging system will then be clinically tested in women with focal breast lesions using histology and KDR staining levels on immunohistochemistry as gold standard. The technology used in this proposal can be integrated on similar other commercial devices beyond the ABVS (in the USA alone, approximately 1600 units are already used in routine clinical practice) and will therefore have immediate impact on the general public.
Current approaches for imaging breast cancer in particular in women with dense breast tissue have major limitations leading to delayed or missed diagnoses as well as false positive results. In this research proposal, we will develop, test, and clinically apply a novel automated and volumetric ultrasound molecular imaging approach to be used as next generation ultrasound imaging technology in women with dense breast tissue. Combining the strength of volumetric ultrasound with molecular imaging capabilities will more accurately diagnose breast cancer.
