Clinical Research Directory

Screening Mammography: Single Reading by One Radiologist With AI vs. Double Reading by Two Radiologists (AI-BCSQ)

A randomized prospective study comparing the evaluation of mammography images in a breast cancer screening programme by a single radiologist with AI support versus standard double reading by two radiologists without AI support.

Breast Density Impact on Mammographic Screening for Breast Cancer Diagnosis

This retrospective, observational study aims to evaluate how breast density affects the accuracy and outcomes of mammographic screening for breast cancer within the regional screening program "Prevenzione Serena". Breast density is an important factor because dense breast tissue can make it more difficult to detect breast cancer on a mammogram. Dense tissue and tumors both appear white on a mammogram, which may hide abnormalities and lead to missed cancers or false-positive results. Women aged 45 to 75 years who underwent routine mammographic screening at ASL CN2 between September 2023 and May 2024 will be included. Breast density will be classified using the BI-RADS system (categories A-D), and the study will assess whether women with dense breasts (categories C and D) experience higher rates of recalls for second-level examinations such as ultrasound, MRI, etc). The study also includes an internal validation of Insight BD, an automated breast-density measurement software used at ASL CN2. The software will be evaluated using a mammography phantom (to verify technical accuracy) and by comparing its BI-RADS density classifications with readings from two radiologists (one expert and one less experienced). This will help determine whether the software can support radiologists, especially in evaluating dense breast tissue. Additional factors such as menopausal status, family history of breast cancer, and hormone therapy will also be examined to understand how they relate to breast density and screening outcomes. The study aims to quantify the frequency of false-positive recalls-cases in which additional tests are recommended but cancer is not found-because these events can increase patient anxiety and healthcare workload. Ultimately, this research seeks to provide evidence that may inform future screening guidelines and support more personalized approaches, particularly for women with dense breasts.

National Mammography Database

The National Mammography Database (NMD) leverages data that radiology practices are already collecting under federal mandate by providing them with comparative information for national and regional benchmarking. Participants receive semi-annual feedback reports that include important benchmark data such as cancer detection rates, positive predictive value rates and recall rates. Participation in the NMD is free to Breast Imaging Center of Excellence (BICOE) facilities.

Contrast Enhancement Mammography vs MRI for the Surveillance of Women at High Risk of Breast Cancer: Con-trust Randomized Controlled Trial

Women at high risk of breast cancer (BC) should undergo annual magnetic resonance imaging (MRI) and digital mammography (DM) from at least ages 35 to 60. While MRI is an expensive and scarce resource, contrast-enhanced mammography (CEM) is a less costly and time-consuming alternative that could be used to screen these women instead of MRI. The Con-TRUST trial aims to randomize 1400 women in 10 centers to test whether CEM can be used instead of MRI+DM for BC detection in high-risk women (\>5% 5-year BC risk). The study will compare efficacy in reducing the incidence of BC in women who tested negative in the first screening and cumulative recall rates over 2 screening rounds. All women will be followed up for 2.5 years. Secondary outcomes include screening performance, safety, and women\'s compliance. The trial results will be integrated with the international literature and proposed for the development of recommendations as part of the adolopment of European guidelines in Italy.