Journal of medical imaging (Bellingham, Wash.) · 2025
Assessing mammographic density change within individuals across screening rounds using deep learning-based software.
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Olinder Jakob, Förnvik Daniel, Dahlblom Victor, Lu Viktor, Åkesson Anna, Johnson Kristin, Zackrisson Sophia
Аннотация
PURPOSE: The purposes are to evaluate the change in mammographic density within individuals across screening rounds using automatic density software, to evaluate whether a change in breast density is associated with a future breast cancer diagnosis, and to provide insight into breast density evolution.
APPROACH: Mammographic breast density was analyzed in women screened in Malmö, Sweden, between 2010 and 2015 who had undergone at least two consecutive screening rounds < 30 months apart. The volumetric and area-based densities were measured with deep learning-based software and fully automated software, respectively. The change in volumetric breast density percentage (VBD%) between two consecutive screening examinations was determined. Multiple linear regression was used to investigate the association between VBD% change in percentage points and future breast cancer, as well as the initial VBD%, adjusting for age group and the time between examinations. Examinations with potential positioning issues were removed in a sensitivity analysis.
RESULTS: In 26,056 included women, the mean VBD% decreased from 10.7% [95% confidence interval (CI) 10.6 to 10.8] to 10.3% (95% CI: 10.2 to 10.3) ( p < 0.001 ) between the two examinations. The decline in VBD% was more pronounced in women with initially denser breasts (adjusted β = - 0.10 , p < 0.001 ) and less pronounced in women with a future breast cancer diagnosis (adjusted β = 0.16 , p = 0.02 ).
CONCLUSIONS: The demonstrated density changes over time support the potential of using breast density change in risk assessment tools and provide insights for future risk-based screening.
APPROACH: Mammographic breast density was analyzed in women screened in Malmö, Sweden, between 2010 and 2015 who had undergone at least two consecutive screening rounds < 30 months apart. The volumetric and area-based densities were measured with deep learning-based software and fully automated software, respectively. The change in volumetric breast density percentage (VBD%) between two consecutive screening examinations was determined. Multiple linear regression was used to investigate the association between VBD% change in percentage points and future breast cancer, as well as the initial VBD%, adjusting for age group and the time between examinations. Examinations with potential positioning issues were removed in a sensitivity analysis.
RESULTS: In 26,056 included women, the mean VBD% decreased from 10.7% [95% confidence interval (CI) 10.6 to 10.8] to 10.3% (95% CI: 10.2 to 10.3) ( p < 0.001 ) between the two examinations. The decline in VBD% was more pronounced in women with initially denser breasts (adjusted β = - 0.10 , p < 0.001 ) and less pronounced in women with a future breast cancer diagnosis (adjusted β = 0.16 , p = 0.02 ).
CONCLUSIONS: The demonstrated density changes over time support the potential of using breast density change in risk assessment tools and provide insights for future risk-based screening.