Characterization of lesions in dense breasts: Does tomosynthesis help?

Area of Science:

• Radiology and Medical Imaging
• Breast Cancer Screening
• Diagnostic Imaging Technologies

Background:

• Mammography faces challenges in dense breasts due to tissue overlap obscuring lesions.
• Digital breast tomosynthesis (DBT) is explored as a potential solution to improve lesion detection and characterization in dense breast tissue.

Purpose of the Study:

• To evaluate the impact of digital breast tomosynthesis (DBT) on characterizing breast lesions across varying mammographic densities.
• To compare the diagnostic performance of mammography alone versus mammography combined with tomosynthesis.

Main Methods:

• A prospective blinded study involved 199 patients with lesions categorized using Breast Imaging Reporting and Data System (BIRADS) on 2D mammograms.
• Radiologists independently assessed lesions using 2D mammography alone, then with the addition of DBT, assigning new BIRADS categories.
• A composite gold standard (histopathology, ultrasound, MRI, follow-up) was used to evaluate categorization accuracy, analyzed across American College of Radiology (ACR) breast density categories.

Main Results:

• Overall, adding DBT to mammography resulted in superior lesion categorization in 21.2% of readings.
• DBT demonstrated the most significant benefit in ACR Density 3 (27% improved categorization) and Density 4 breasts (42% improved categorization).
• Diagnostic confidence increased with DBT in 54.5% of lesions in ACR Density 3 and 63.6% in ACR Density 4 breasts.

Conclusions:

• The utility of tomosynthesis in a diagnostic setting increases proportionally with breast density.
• DBT is particularly valuable in higher breast density categories, potentially altering patient management.
• This study identifies patient subgroups where DBT can significantly improve diagnostic outcomes.