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Assessing mammographic density change within individuals across screening rounds using deep learning-based software.

Jakob Olinder1,2, Daniel Förnvik3,4, Victor Dahlblom1,2

  • 1Lund University, Department of Translational Medicine, Radiology Diagnostics, Malmö, Sweden.

Journal of Medical Imaging (Bellingham, Wash.)
|August 18, 2025
PubMed
Summary
This summary is machine-generated.

Breast density naturally decreases over time, particularly in women with denser breasts. A slower decline in breast density may indicate a higher risk of future breast cancer diagnosis.

Keywords:
breast cancer riskbreast cancer screeningbreast densitydeep learninglongitudinal trendsmammography

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Area of Science:

  • Radiology and Imaging Science
  • Oncology
  • Biostatistics

Background:

  • Mammographic breast density is a significant risk factor for breast cancer.
  • Understanding breast density changes over time is crucial for accurate risk assessment.

Purpose of the Study:

  • To evaluate changes in mammographic density within individuals across screening rounds using automated software.
  • To determine if changes in breast density are associated with future breast cancer diagnosis.
  • To provide insights into the evolution of breast density over time.

Main Methods:

  • Analysis of mammographic breast density in women screened between 2010 and 2015 with at least two screening rounds.
  • Measurement of volumetric breast density percentage (VBD%) using deep learning-based software.
  • Investigation of the association between VBD% change and future breast cancer using multiple linear regression, adjusting for covariates.

Main Results:

  • A total of 26,056 women were included in the study.
  • Mean VBD% decreased from 10.7% to 10.3% between screenings (p < 0.001).
  • The decline in VBD% was more pronounced in women with initially denser breasts but less pronounced in those with future breast cancer diagnoses.

Conclusions:

  • Observed changes in breast density over time can enhance risk assessment tools.
  • These findings offer valuable insights for developing future risk-based screening strategies.
  • Monitoring breast density evolution is important for personalized breast cancer risk evaluation.