SBIR Phase II: Enhanced Medical Ultrasound for Breast Cancer Imaging

The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase II project is to address the need for alternative imaging technologies for women with mammographically dense breast tissue by significantly enhancing clinical breast ultrasound images. Mammography is the gold standard for breast cancer screening; however, both dense breast tissue and cancerous lesions appear white on a mammogram, making it difficult to reliably detect cancers. Women who have dense tissue - 26 million in the United States alone - need alternative imaging technologies for early stage cancer detection. Studies show that the addition of a single screening ultrasound increases cancer detection by 28% over mammography alone, with significantly higher combined diagnostic accuracy. Despite these findings, a fourfold increase in the false positive rate undermines ultrasound use by physicians in breast imaging. A technology that improves ultrasound image clarity in dense breast tissue would revolutionize breast cancer imaging by allowing physicians to noninvasively detect malignancies previously obscured by their size and/or poor contrast and distinguish them from benign lesions. There is the strong potential to save lives by substantially increasing the overall cancer detection rate while simultaneously reducing the number of false positives. The proposed project seeks to develop an adaptive beamforming technology that will significantly improve the clinical utility of ultrasound imaging. Unlike traditional beamforming, adaptive beamforming estimates the time delays between ultrasound probe elements and does not require prior knowledge of the speed of sound along the beam path to produce an image of the tissue. The more accurate time delays result in improved beam focusing and allow for larger transducer arrays, which in turn allows for deeper signal penetration - enhancing signal strength, spatial resolution, and image contrast. The preceding Phase I project used simulated ultrasound data to develop a novel adaptive beamforming technique with least-mean square filters that improves signal-to-noise ratio by up to 32 dB and image contrast by up to 38%. The Phase II project objectives are to acquire raw, radio-frequency ultrasound data from both representative breast phantoms and an in vivo study; to optimize and finalize the adaptive beamforming algorithm; to process the study data and evaluate improved image contrast and clinical benefit; to produce a software application embodying the adaptive beamforming technique; and to design the network architecture and data management approach required to deliver that software as a license or as a Software as a Service (SaaS) product to medical facilities.