Mammographic parenchymal patterns and mode of detection: implications for the breast screening programme

Area of Science:

• Radiology and Oncologic Imaging
• Breast Cancer Screening Research
• Epidemiology of Cancer

Background:

• Mammographic parenchymal patterns, classified using Wolfe's system, are known indicators of breast density.
• Dense breast tissue can obscure tumors, potentially reducing mammography's sensitivity.
• The association between specific parenchymal patterns and breast cancer risk, especially concerning screening outcomes, requires further investigation.

Purpose of the Study:

• To evaluate how mammographic parenchymal patterns influence the risk of breast cancer detection at different stages of screening.
• To determine if certain parenchymal patterns affect the likelihood of detecting breast cancer during the first screen, second screen, or in the interval between screenings.

Main Methods:

• A nested case-control study was conducted within a cohort undergoing breast cancer screening in East Anglia.
• The study included cases of breast cancer detected at prevalence screening, interval cancers, and first incidence screens, matched with controls.
• Mammographic parenchymal patterns were assessed using Wolfe's classification, with statistical analysis performed via conditional logistic regression.

Main Results:

• A significant proportion of both patients (67%) and controls (59%) exhibited high-risk mammographic patterns (P2 + DY).
• High-risk patterns (P2, DY) were associated with a greater risk of interval cancers (ORs 2.2-2.4) compared to screen-detected cancers (ORs 1.7-1.1).
• The risk was particularly elevated for interval cancers within 18 months of a negative mammogram (ORs 3.8-4.1) and was concentrated in high-grade (grade III) invasive ductal carcinomas.

Conclusions:

• Mammographic parenchymal patterns, specifically dense patterns (P2, DY), are linked to reduced screening effectiveness.
• These high-risk patterns are associated with a higher incidence of aggressive, high-grade breast cancers.
• Improving screening sensitivity for dense breasts and enhancing the diagnosis of high-grade tumors are crucial for optimizing breast cancer detection outcomes.