"While early detection of breast cancer by screening appears effective, many women derive little or no benefit from screening, due to the way it is currently organized: as a one-size-fits all approach irrespective of personalised risk factors. It is known, however, that some women are at a much higher risk of getting the disease than others, and that mammography is unsuitable for cancer detection in women with dense breasts. The aim of this project is to develop personalised methods to tailor breast cancer screening to the individual needs of the woman. We will propose methods to stratify women at the highest risk to MRI; those with intermediate risk and/or dense breasts to follow-on ultrasound. A risk model will be developed that includes both breast cancer risk and the risk of missing cancers in mammograms. In this model, breast density plays a key role, as one of the largest known risk factors and the factor making mammograms ineffective. Two SMEs focusing on breast density are involved, where academic partners bring unique databases with over 80,000 screening mammograms and associated risk profiles. These are essential for model development, and subsequently for the development of products that benefit all women. Personalised screening is only economically feasible if it is based upon cost-effective strategies. While current methods in breast MRI imaging and breast ultrasound are promising, more efficient protocols must be developed to use these modalities routinely in screening. With leading SMEs and clinical partners, screening procedures will be optimized by developing automated image analysis tools to guide workflow and quality assurance. More efficient MRI protocols will be investigated to reduce time and cost, while the use of novel MRI imaging sequences without intravenous contrast will be explored. Cost-effectiveness of the stratification models will be assessed by combining the risk model with cost and effectiveness of alternative screening strategies."