Mammographic texture versus conventional Cumulus measure of density in breast cancer risk prediction: a literature review.

Abstract

Mammographic textures show promise as breast cancer risk predictors, distinct from mammographic density. Yet, it lacks comprehensive evidence to determine the stronger risk predictor between textures and density, and the reliability of texture-based measures. We searched PubMed database for research publications, published up to November 2023, which assessed breast cancer risk associations(odds ratios[OR]) with texture-based measures and percent mammographic density(PMD), and their discrimination(area under the receiver operating characteristics curve[AUC]), using same datasets. Of 11 publications, for textures, six found stronger associations(P<0.05) with 11%-508% increases on log scale by study and four found weaker associations(P<0.05) with 14%-100% decreases, compared with PMD. Risk associations remained significant when fitting textures and PMD together. Eleven of 17 publications show greater AUCs for textures than PMD(P<0.05); increases were 0.04-0.25 by study. Discrimination of PMD and these textures jointly was significantly higher than PMD alone (P<0.05). Therefore, different textures could capture distinct breast cancer risk information, partially independent of mammographic density, suggesting their joint role in breast cancer risk prediction. Certain textures could outperform mammographic density for predicting breast cancer risk. However, obtaining reliable texture-based measures necessitates addressing various issues. Collaboration of researchers from diverse fields could be beneficial for advancing this complex field.