Breast Density Impact on Mammographic Screening for Breast Cancer Diagnosis

Plain-language summary

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.

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