ArticleLa Radiologia medica2024
Background parenchymal enhancement on contrast-enhanced mammography: associations with breast density and patient's characteristics.
Article in La Radiologia medica, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
15 citing papers in PubMed.
- Decoupling Structural and Vascular Biomarkers in Contrast-Enhanced Mammography: A Methodological Synthesis and Perspective.Diagnostics (Basel, Switzerland) · 2026Article
- ROI-Based Quantitative Analysis in Contrast-Enhanced Mammography: A Feasibility Study for Reproducible Enhancement Assessment.Diagnostics (Basel, Switzerland) · 2026Article
- Review
- How to optimise breast cancer staging with contrast-enhanced mammography: current evidence and clinical implications.Insights into imaging · 2026Review
- Use of contrast-enhanced mammography for preoperative prediction of lymphovascular invasion status in invasive breast cancer.Cancer imaging : the official publication of the International Cancer Imaging Society · 2026Article
- Clinically Robust Deep Learning for Contrast-Enhanced Mammography: Multicenter Evaluation Across Convolutional Neural Network Architectures.Bioengineering (Basel, Switzerland) · 2026Article
- Establishment of prediction model for breast lesion using automated breast ultrasound system.Quantitative imaging in medicine and surgery · 2026Article
- Engineering the Image Representation for Deep Learning in Contrast-Enhanced Mammography: A Systematic Analysis of Preprocessing and Anatomical Masking.Bioengineering (Basel, Switzerland) · 2026Article
- Beyond Cancer Detection: An AI Framework for Multidimensional Risk Profiling on Contrast-Enhanced Mammography.Diagnostics (Basel, Switzerland) · 2025Article
- Contrast-enhanced spectral mammography demonstrates better inter-reader repeatability than digital mammography for screening breast cancer patients.Journal of medical imaging (Bellingham, Wash.) · 2025Article
- Article
- Contrast-enhanced mammography for breast cancer detection and diagnosis with high concentration iodinated contrast medium.Insights into imaging · 2025Article
- Morphodynamic Features of Contrast-Enhanced Mammography and Their Correlation with Breast Cancer Histopathology.Journal of imaging · 2025Article
- Factors Influencing Background Parenchymal Enhancement in Breast Contrast-Enhanced Mammography: A Retrospective Study.International journal of women's health · 2025Article
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposeTo evaluate if background parenchymal enhancement (BPE) on contrast-enhanced mammography (CEM), graded according to the 2022 CEM-dedicated Breast Imaging Reporting and Data System (BI-RADS) lexicon, is associated with breast density, menopausal status, and age.
methodsThis bicentric retrospective analysis included CEM examinations performed for the work-up of suspicious mammographic findings. Three readers independently and blindly evaluated BPE on recombined CEM images and breast density on low-energy CEM images. Inter-reader reliability was estimated using Fleiss κ. Multivariable binary logistic regression was performed, dichotomising breast density and BPE as low (a/b BI-RADS categories, minimal/mild BPE) and high (c/d BI-RADS categories, moderate/marked BPE).
resultsA total of 200 women (median age 56.8 years, interquartile range 50.5-65.6, 140/200 in menopause) were included. Breast density was classified as a in 27/200 patients (13.5%), as b in 110/200 (55.0%), as c in 52/200 (26.0%), and as d in 11/200 (5.5%), with moderate inter-reader reliability (κ = 0.536; 95% confidence interval [CI] 0.482-0.590). BPE was minimal in 95/200 patients (47.5%), mild in 64/200 (32.0%), moderate in 25/200 (12.5%), marked in 16/200 (8.0%), with substantial inter-reader reliability (κ = 0.634; 95% CI 0.581-0.686). At multivariable logistic regression, premenopausal status and breast density were significant positive predictors of high BPE, with adjusted odds ratios of 6.120 (95% CI 1.847-20.281, p = 0.003) and 2.416 (95% CI 1.095-5.332, p = 0.029) respectively.
conclusionBPE on CEM is associated with well-established breast cancer risk factors, being higher in women with higher breast density and premenopausal status.
Indexed as
Identifiers
39060886What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.