Digital screening mammograms: current status and future prospects

Area of Science:

• Radiology and Medical Imaging
• Oncology
• Biomedical Engineering

Background:

• Mammography is a vital breast cancer screening tool, but faces limitations like reduced sensitivity in dense breasts and overdiagnosis.
• Emerging technologies aim to overcome these challenges and enhance screening efficacy.

Purpose of the Study:

• To review emerging mammography technologies and their assessment endpoints.
• To evaluate the clinical impact of digital breast tomosynthesis (DBT), contrast-enhanced mammography (CEM), and artificial intelligence (AI) in mammography.

Main Methods:

• Review of clinical trial data for DBT, focusing on interval and advanced cancer rates.
• Assessment of CEM as a supplemental screening tool for dense breasts.
• Overview of AI applications in mammography for lesion detection, triage, density assessment, and risk prediction.

Main Results:

• Emerging technologies show improved surrogate endpoints like cancer detection.
• Evidence for reducing clinically meaningful outcomes (interval/advanced cancers) is still developing.
• DBT performance varies between average-risk and high-risk populations.

Conclusions:

• While new mammography technologies improve cancer detection, their effect on reducing interval and advanced cancers needs more robust evidence.
• Future research must prioritize clinically relevant endpoints and real-world validation to ensure patient benefit.