Rationale And Objectives: To explore radiological aspects of interval breast cancer in a population-based screening program.
Materials And Methods: We performed a consensus-based informed review of mammograms from diagnosis and prior screening from women diagnosed with interval cancer 2004-2016 in BreastScreen Norway. Cases were classified as true (no findings on prior screening mammograms), occult (no findings at screening or diagnosis), minimal signs (minor/non-specific findings) and missed (obvious findings).
Purpose To compare the performance of digital breast tomosynthesis (DBT) and two-dimensional synthetic mammography (SM) with that of digital mammography (DM) in a population-based mammographic screening program. Materials and Methods In this prospective cohort study, data from 37 185 women screened with DBT and SM and from 61 742 women screened with DM as part of a population-based screening program in 2014 and 2015 were included. Early performance measures, including recall rate due to abnormal mammographic findings, rate of screen-detected breast cancer, positive predictive value of recall, positive predictive value of needle biopsy, histopathologic type, tumor size, tumor grade, lymph node involvement, hormonal status, Ki-67 level, and human epidermal growth factor receptor 2 status were compared in women who underwent DBT and SM screening and in those who underwent DM screening by using χ tests, two-sample unpaired t tests, and tests of proportions.
View Article and Find Full Text PDFBackground: Increased understanding of the variability in normal breast biology will enable us to identify mechanisms of breast cancer initiation and the origin of different subtypes, and to better predict breast cancer risk.
Methods: Gene expression patterns in breast biopsies from 79 healthy women referred to breast diagnostic centers in Norway were explored by unsupervised hierarchical clustering and supervised analyses, such as gene set enrichment analysis and gene ontology analysis and comparison with previously published genelists and independent datasets.
Results: Unsupervised hierarchical clustering identified two separate clusters of normal breast tissue based on gene-expression profiling, regardless of clustering algorithm and gene filtering used.
Introduction: Mammographic density (MD), as assessed from film screen mammograms, is determined by the relative content of adipose, connective and epithelial tissue in the female breast. In epidemiological studies, a high percentage of MD confers a four to six fold risk elevation of developing breast cancer, even after adjustment for other known breast cancer risk factors. However, the biologic correlates of density are little known.
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