7. Breast cancer is the most common cancer worldwide and the most common cancer diagnosed in Americanwomen. While there has been good progress regarding detection and treatment methods, breast cancer remainsthe primary cause of death from malignant tumors. Hence, there is a critical need for the development of novelpredictive and prognostic factors. Risk assessments are currently performed by medical professionals to identifywomen that could benefit from enhanced breast surveillance or risk reduction methods. Unfortunately, mostdiagnosed cases do not have an identifiable risk factor, making it a challenge to identify high risk women prior toonset using classical risk assessments. This medical difficulty has resulted in the development of several artificialintelligence and machine learning approaches being applied to screening mammograms to identify breast cancerearlier. However, these approaches search for abnormalities that indicate an existing cancer and have beenfound to not be generalizable to the entire screening population. It is becoming more common for younger womento be diagnosed with breast cancer, and the cancers tend to be more aggressive. This Phase I proposes tocreate a risk assessment product for mammography that is not based on machine learning but rather a novelmeasurement of risky dense tissue. Alteration in the architecture and composition of microenvironment is a well-recognized component of breast pathologies and some changes may occur prior to tumor onset. WAVEDMedical's measurement is sensitive to these alternations in identifying areas of dense tissue that is tumor prone.This feasibility study seeks to demonstrate that the novel measurement of risky dense breast tissue has thepotential to be implemented into classical risk models. Phase I specific aims are to 1) improve efficiency inidentifying risky dense tissue on mammograms by creating a secure database that contains preprocessed datafor optimized analysis, and 2) establish risky dense tissue as a better predictor of breast cancer than traditionalmammographic percent density (MPD), by showing risky dense tissue is more accurate in predicting breastcancer than MPD. Follow-on Phase II efforts will include developing a platform and integrating WAVED intohospital infrastructure for evaluating mammograms. These improvements will create a risk assessment productthat increases the accuracy of medical professionals at identifying high-risk patients and ensures patients arereceiving additional medical care, such as supplemental screening or risk reduction methods, to prevent invasivecancer. Successful completion of the project has potential to advance state-of-the-art breast cancer assessmentsto provide quantification of risky dense tissue to identify high-risk patients needing preventive care.
Public Health Relevance Statement: 8. PROJECT NARRATIVE
Traditional breast cancer risk assessments remain insufficient for identifying women at high-risk prior to
discovery, even when accounting for high breast density, since most diagnosed cases do not have an identifiable
risk factor. WAVED Medical's image-based risk assessment technology identifies high-risk women by quantifying
the amount of risky dense mammographic tissue in a screening setting to provide a more accurate and objective
risk estimation. Medical professionals can proactively stratify risk and recommend preventive care rather than
reactive treatments to improve patient outcomes.
Project Terms:
