Long term follow-up of women treated for screen detected atypical ductal hyperplasia or lobular neoplasia in a large UK screening centre.

Background: Atypical ductal hyperplasia (ADH) and lobular neoplasia (LN) increase subsequent breast cancer (BC) risk. However, optimal surveillance and risk reduction regimes remain uncertain. We report management and outcomes of women with ADH and LN to provide data on potential screening/prevention strategies.

Breast density prediction from low and standard dose mammograms using deep learning: effect of image resolution and model training approach on prediction quality.

. To improve breast cancer risk prediction for young women, we have developed deep learning methods to estimate mammographic density from low dose mammograms taken at approximately 1/10th of the usual dose. We investigate the quality and reliability of the density scores produced on low dose mammograms focussing on how image resolution and levels of training affect the low dose predictions.

Artificial Intelligence for Image-Based Breast Cancer Risk Prediction Using Attention.

Accurate prediction of individual breast cancer risk paves the way for personalised prevention and early detection. The incorporation of genetic information and breast density has been shown to improve predictions for existing models, but detailed image-based features are yet to be included despite correlating with risk. Complex information can be extracted from mammograms using deep-learning algorithms, however, this is a challenging area of research, partly due to the lack of data within the field, and partly due to the computational burden.

Germline testing of , , and c.1100delC in 1514 triple negative familial and isolated breast cancers from a single centre, with extended testing of , and in over 400.

Background: The identification of germline pathogenic gene variants (PGVs) in triple negative breast cancer (TNBC) is important to inform further primary cancer risk reduction and TNBC treatment strategies. We therefore investigated the contribution of breast cancer associated PGVs to familial and isolated invasive TNBC.

Methods: Outcomes of germline , and _c.