Abstract
This study evaluated the performance of supplemental automated breast ultrasound (ABUS) in women with negative screening mammographic findings and assessed its utility across clinical subgroups to inform personalized implementation strategies. Methods: We retrospectively identified 3,417 ABUS examinations performed concurrently with mammography between January 2022 and April 2024. Examinations with negative mammographic findings were included, while those with positive mammographic findings, no workup for ABUS-positive results, or less than 12 months of follow-up were excluded. The reference standards were histopathology and 12-month follow-up outcomes. ABUS performance was evaluated overall and within subgroups stratified by age (<50 vs. ≥50 years), mammographic density (non-dense vs. dense), body mass index (<25 vs. ≥25 kg/m2), and prior ultrasound history (prevalence vs. incidence). Results: We analyzed 1,932 ABUS examinations from 1,597 women (mean age, 56±9 years). ABUS detected 13 cancers, yielding a detection rate of 6.7 per 1,000. Of these, 11 (84.6%) were invasive, including nine (81.8%) node-negative lesions, with a median size of 1.2 cm (range, 0.1 to 2.6 cm). One interval cancer was identified as a palpable mass 8 months after a negative ABUS examination. The abnormal interpretation rate, biopsy rate, sensitivity, and specificity were 28.0% (542/1,932), 4.0% (78/1,932), 92.9% (13/14), and 72.4% (1,389/1,918), respectively. Higher abnormal interpretation rates and lower specificity were observed among women aged <50 years, those with dense breasts, and during prevalence examinations. No cancers were detected in women with non-dense breasts. Conclusion: ABUS identified small, node-negative invasive cancers with likely favorable prognoses but demonstrated limited value in women with non-dense breasts, supporting its personalized use based on breast density and patient preference.
| Original language | English |
|---|---|
| Pages (from-to) | 18-29 |
| Number of pages | 12 |
| Journal | Ultrasonography |
| Volume | 45 |
| Issue number | 1 |
| DOIs | |
| Publication status | Published - 2026 Jan |
Bibliographical note
Publisher Copyright:© 2026 Korean Society of Ultrasound in Medicine (KSUM).
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
Keywords
- Automated breast ultrasound
- Density
- Mammography
- Screening
ASJC Scopus subject areas
- Radiology Nuclear Medicine and imaging
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