.png){kind=icon}
.png){kind=icon}
Return
Lesion Detectability and Masking Disparity Assessment in Breast Tomosynthesis Across Diverse Populations Using In-Silico Imaging Trials
.png){kind=icon}
PRE
AI
B
R
V
H
Q
M
P
P
S
A
A
DOI：10.1109/tmi.2026.3701599.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
Breast density impacts cancer detection by masking tumors within fibroglandular tissue and there are disparities in screening outcomes across racial groups. However, it remains unclear whether these differences reflect inherent tissue characteristics or systemic bias. To isolate the effect of breast density on lesion detectability across racial subgroups, we conducted a retrospective case-control study using raw tomosynthesis projections from 902 women (453 cases, 451 matched controls) across BI-RADS density categories and self-reported race. Identical <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">in-silico</i> spiculated masses (8–15 mm) and microcalcification clusters (10–14 mm) were inserted into the projections using a calibrated lesion model. Images were reconstructed in the same manner to avoid proprietary processing in lesion detection. Lesion detectability was assessed with Channelized Hotelling Observers. Regression and causal mediation analyses examined the relationships between race, density, and detectability. As result, detectability decreased with increasing density; for masses, the area under the receiver operating characteristic curve (ROC AUC) reduced significantly from 0.93 to 0.85 (BIRADS A to D), whereas for microcalcifications AUC decreased from 0.85 to 0.78 across the same density range. Discrimination remained higher for masses than calcifications (AUC = 0.89 vs. AUC = 0.82). Stratified analyses showed slightly higher detectability in Non-Hispanic Black women compared with Non-Hispanic White and Asian American women, largely reflecting differences in density. Mediation analysis revealed that breast density accounted for 38–55% of the observed race-associated detectability differences. Mediation analyses have shown that density is the dominant factor in detectability. These findings support the development of calibrated detection models and personalized screening strategies that account for breast density.
Keywords:
Digital breast tomosynthesis
virtual imaging trials
lesion detection
breast cancer
Journal
IF:
9.8
Papers:
6.2K
Citations:
3.7W
Organization
Cited Papers