Age-related change in mammographic breast density of women without history of breast cancer over a 10-year retrospective study

Abstract

Background Women with higher breast density are at higher risk of developing breast cancer. Breast density is known to affect sensitivity to mammography and to decrease with age. However, the age change and associated factors involved are still unknown. This study aimed to investigate changes in breast density and the associated factors over a 10-year period. Materials and Methods The study included 221 women who had undergone eight or more mammograms for 10 years (2011–2020), were between 25 and 65 years of age, and had no abnormalities as of 2011. Breast density on mammographic images was classified into four categories: fatty, scattered, heterogeneously dense, and extremely dense. Breast density was determined using an image classification program with a Microsoft Lobe’s machine-learning model. The temporal changes in breast density over a 10-year period were classified into three categories: no change, decrease, and increase. An ordinal logistic analysis was performed with the three groups of temporal changes in breast density categories as the objective variable and the four items of breast density at the start, BMI, age, and changes in BMI as explanatory variables. Results As of 2011, the mean age of the 221 patients was 47 ± 7.3 years, and breast density category 3 scattered was the most common (67.0%). The 10-year change in breast density was 64.7% unchanged, 25.3% decreased, and 10% increased. BMI was increased by 64.7% of women. Breast density decreased in 76.6% of the category at the start: extremely dense breast density at the start was correlated with body mass index (BMI). The results of the ordinal logistic analysis indicated that contributing factors to breast density classification were higher breast density at the start (odds ratio = 0.044; 95% CI [0.025–0.076]), higher BMI at the start (odds ratio = 0.76; 95% CI [0.70–0.83]), increased BMI (odds ratio = 0.57; 95% CI [0.36–0.92]), and age in the 40s at the start (odds ratio = 0.49; 95% CI [0.24–0.99]). No statistically significant differences were found for medical history. Conclusion Breast density decreased in approximately 25% of women over a 10-year period. Women with decreased breast density tended to have higher breast density or higher BMI at the start. This effect was more pronounced among women in their 40s at the start. Women with these conditions may experience changes in breast density over time. The present study would be useful to consider effective screening mammography based on breast density.

AI-based Apoptosis Cell Classification Using Phase-contrast Images of K562 Cells

“…As AI is known to classify images in ways different from the human naked eye, when AI will be able to classify the cells without dynamic (time-lapse) information, a gate for quick high-throughput cell classification could be opened. Lobe, a machine-learning model development software developed by Microsoft, operates on a PC and allows users to create their own classification system by training at least five images per label (20). A data set or training data including normal and apoptotic cell images, should be produced to teach an AI.…”