Evaluation and Reclassification of ( BI-RADS 3) Breast Lesions in Dense Breast

BI-RADS category 3 lesions are considered probably benign findings but generally require short-interval imaging follow-up to document stability. This may result in additional examinations and patient anxiety. The study will investigate the role of digital breast tomosynthesis (DBT) compared with combined ultrasound (US) and digital mammography (DM) in the assessment and reclassification of these lesions, particularly in patients with dense breast tissue.

This is a prospective study to be conducted at Sohag University Hospital. The study population will consist of 30 female patients presenting with at least one non-calcified breast lesion initially classified as BI-RADS 3 on standard 2D digital mammography. Patients with breast densities B, C, or D will be eligible, with particular consideration of dense breasts (C and D).

All patients will undergo baseline 2D digital mammography, followed by complementary targeted breast ultrasound using a high-resolution linear-array transducer. Ultrasound assessment will include evaluation of lesion shape, orientation, margins, echo pattern, and posterior acoustic features, with a separate US-based BI-RADS assessment.

Patients will also undergo digital breast tomosynthesis using standard bilateral craniocaudal and mediolateral oblique views, with reconstruction into 1-mm slices. DBT assessment will include evaluation of lesion margins and assessment for associated architectural distortion or microcalcifications that may not be apparent on 2D mammography. A separate DBT-based BI-RADS assessment will be assigned.

The imaging findings will subsequently undergo an integrated assessment. The protocol includes independent assessment of US and DBT findings followed by assignment of a final BI-RADS category based on the combined findings. Reclassification may include downgrading a finding when DBT demonstrates that an apparent mammographic asymmetry represents overlapping normal breast tissue, or upgrading a lesion when suspicious ultrasound features such as non-parallel orientation or angular margins are identified.

Diagnostic performance measures, including sensitivity, specificity, positive predictive value, and negative predictive value, will be calculated for US and DBT. Data will be analyzed using SPSS software.