ReviewKorean journal of radiology2020
Automated Breast Ultrasound Screening for Dense Breasts.
Review in Korean journal of radiology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 50 papers, 1 of them a synthesis that pooled it.
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
50 citing papers in PubMed, 1 synthesis or guideline pooled it, 82 citations in OpenAlex.
- A systematic review and meta-analysis comparing the diagnostic capability of automated breast ultrasound and contrast-enhanced ultrasound in breast cancer.Frontiers in oncology · 2023Pooled it
- Comparison of automated breast ultrasound and hand-held breast ultrasound in preoperative evaluation of early-stage breast cancer: a multicenter prospective study.European radiology · 2026Article
- Automated breast ultrasound (ABUS) meets artificial intelligence: a new accurate classification tool for BIRADS 3-4 breast lesions.Journal of ultrasound · 2026Article
- Automated breast ultrasound (ABUS) versus handheld ultrasound (HHUS) for the preoperative assessment of tumor size in invasive breast cancer.Journal of ultrasound · 2026Article
- Energy sustainability of breast ultrasound: comparison of automated and handheld ultrasound systems.Ultrasonography (Seoul, Korea) · 2026Article
- Response to "Automated Breast Ultrasound in Dense-Breast Screening: Beyond Additional Cancer Detection".Korean journal of radiology · 2026Article
- Deep learning-based Breast Imaging Reporting and Data System classification and establishment of diagnostic model in breast cancer diagnosis with automated breast ultrasound.Quantitative imaging in medicine and surgery · 2026Article
- The additive value of 3D automated breast ultrasound and contrast enhanced spectral mammography in the assessment of suspicious breast lesions.Journal of the Egyptian National Cancer Institute · 2026Article
- Beyond mammography: Superior performance of ultrasound in early-onset breast cancer implications for age-specific, density-tailored screening.Turkish journal of surgery · 2026Article
- Comparison of Digital Mammography Plus Full ABUS Review and Digital Mammography Plus Selective ABUS Review Guided by ABUS Artificial Intelligence-Computer-Aided Diagnosis for Breast Cancer Screening.Korean journal of radiology · 2026Article
- ABUS-based glandular tissue component classification for breast cancer risk prediction in Chinese women with dense breasts: a retrospective study.BMC medical imaging · 2026Article
- Machine Learning-Based Ultrasound Radiomics Signature: A Retrospective Analysis for Differentiating Benign from Malignant Non-Mass Lesions in Dense Breasts.International journal of general medicine · 2026Article
- Supplemental automated breast ultrasound in negative screening mammography: early-stage cancer detection in dense breasts with limited yield in non-dense breasts.Ultrasonography (Seoul, Korea) · 2026Article
- Screening Outcomes of Supplemental Automated Breast Ultrasound in Women With Nondense Breasts Undergoing Mammography.Korean journal of radiology · 2026Article
- Effectiveness of AI-CAD Software for Breast Cancer Detection in Automated Breast Ultrasound.Journal of imaging informatics in medicine · 2025Article
- Study on ABUS Applicability for Rural Women With Low Health Resources in China-Large-Scale Population, Non-Opportunistic Screening.Journal of ultrasound in medicine : official journal of the American Institute of Ultrasound in Medicine · 2025Article
- Breast Cancer Screening in Asian Countries: Epidemiology, Screening Practices, Outcomes, Challenges, and Future Directions.Korean journal of radiology · 2025Review
- A nomogram for diagnosis of BI-RADS 4 breast nodules based on three-dimensional volume ultrasound.BMC medical imaging · 2025Article
- Artificial Intelligence in Diagnostic Breast Ultrasound: A Comparative Analysis of Decision Support Among Radiologists With Various Levels of Expertise.European journal of breast health · 2025Article
- Improving diffuse optical tomography imaging quality using APU-Net: an attention-based physical U-Net model.Journal of biomedical optics · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Mammography is the primary screening method for breast cancers. However, the sensitivity of mammographic screening is lower for dense breasts, which are an independent risk factor for breast cancers. Automated breast ultrasound (ABUS) is used as an adjunct to mammography for screening breast cancers in asymptomatic women with dense breasts. It is an effective screening modality with diagnostic accuracy comparable to that of handheld ultrasound (HHUS). Radiologists should be familiar with the unique display mode, imaging features, and artifacts in ABUS, which differ from those in HHUS. The purpose of this study was to provide a comprehensive review of the clinical significance of dense breasts and ABUS screening, describe the unique features of ABUS, and introduce the method of use and interpretation of ABUS.
Indexed as
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What 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.