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Peer-Reviewed Publication
Biom J2026;68(3):e70135.June 1, 2026Journal Article

The DeepJoint Algorithm: An Innovative Approach for Studying the Longitudinal Evolution of Quantitative Mammographic Density and Its Association With Screen-Detected Breast Cancer Risk.

Manel Rakez1, Julien Guillaumin2, Aurelien Chick2, Gaelle Coureau3,4, Foucauld Chamming's5, Pierre Fillard2, Brice Amadeo3, Virginie Rondeau1
1BIOSTAT Team, Bordeaux Population Health, U1219, ISPED, Bordeaux, France.
2Therapixel, Nice, France.
3EPICENE Team, Bordeaux Population Health, U1219, ISPED, Bordeaux, France.
4Department of Public Health, Bordeaux University Hospital, Bordeaux, France.
5Department of Radiology, Institut Bergonié, Comprehensive Cancer Centre, Bordeaux, France.
PubMed PMC DOI PDF

Abstract

High mammographic density is a well-known risk factor for breast cancer and reduces the sensitivity of mammography-based screening. While automated machine and deep learning-based methods provide more consistent and precise measurements compared to subjective Breast Imaging Reporting and Data System (BI-RADS) assessments, they often fail to account for the longitudinal evolution of density. Many o…

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