BREAST CANCER RISK AND DETECTION USING GENES, MAMMOGRAPHIC DENSITY AND MAMMOGRAMS

Abstract

BREAST CANCER IS THE MOST COMMON CANCER AMONG WOMEN IN SINGAPORE. RISK PREDICTION WHICH FACILITATES INDIVIDUALIZED PRIMARY PREVENTION STRATEGIES, AND MORE ACCURATE DIAGNOSIS OF THE DISEASE ARE NEEDED TO REDUCE ITS HEALTHCARE BURDEN. HOWEVER, CURRENT TOOLS FOR RISK PREDICTION AND LESION CHARACTERIZATION ARE IMPRECISE. THIS THESIS EVALUATES THE POTENTIAL OF INCORPORATING QUANTITATIVE MEASURES OF MAMMOGRAPHIC DENSITY OBTAINED VIA AN AUTOMATED APPROACH, AS WELL AS COMMON GENETIC RISK VARIANTS TO AN ESTABLISHED BREAST CANCER RISK ASSESSMENT MODEL. WE FOUND THAT THE INCLUSION OF BOTH FACTORS CAN INCREASE THE DISCRIMINATORY ACCURACY OF TRADITIONAL MODELS AMONG FEMALES IN SINGAPORE. THE USE OF STEREOSCOPIC DIGITAL MAMMOGRAPHY (SDM), A NEW THREE-DIMENSIONAL MODE OF DIAGNOSTIC IMAGING IS ALSO EXPLORED HERE. SDM IMPROVED THE CONSPICUITY OF MASS LESIONS AND DECREASED THE NEED FOR ADDITIONAL FOLLOW-UP PROCEDURES. OVERALL, WE HAVE DEMONSTRATED THE APPLICATION OF AN UPDATED RISK ASSESSMENT METHOD AND