ArticleJournal of ultrasound2021
S-Detect characterization of focal solid breast lesions: a prospective analysis of inter-reader agreement for US BI-RADS descriptors.
Article in Journal of ultrasound, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed.
- Optimizing S-detect classification accuracy for BI-RADS 4 breast nodules using multimodal ultrasound parameters.Quantitative imaging in medicine and surgery · 2026Article
- The Clinical Application of Artificial Intelligence in Breast Imaging: Current Insights, Challenges, and Future Directions.Journal of breast cancer · 2025Review
- Clinical Application of Artificial Intelligence in Breast Ultrasound.Journal of the Korean Society of Radiology · 2025Review
- Comparative Study of AI Modes in Ultrasound Diagnosis of Breast Lesions.Diagnostics (Basel, Switzerland) · 2025Article
- Artificial intelligence-based, semi-automated segmentation for the extraction of ultrasound-derived radiomics features in breast cancer: a prospective multicenter study.La Radiologia medica · 2024Article
- Artificial intelligence in breast ultrasound: application in clinical practice.Ultrasonography (Seoul, Korea) · 2024Article
- Recent Advances in Ultrasound Breast Imaging: From Industry to Clinical Practice.Diagnostics (Basel, Switzerland) · 2023Review
- No sonographer, no radiologist: Assessing accuracy of artificial intelligence on breast ultrasound volume sweep imaging scans.PLOS digital health · 2022Article
- Can strain US-elastography with strain ratio (SRE) improve the diagnostic accuracy in the assessment of breast lesions? Preliminary results.Journal of ultrasound · 2021Article
- Accuracy of mammography and ultrasonography and their BI-RADS in detection of breast malignancy.Caspian journal of internal medicine · 2021Article
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7 authors.
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Abstract
backgroundTo assess inter-reader agreement for US BI-RADS descriptors using S-Detect: a computer-guided decision-making software assisting in US morphologic analysis.
methods73 solid focal breast lesions (FBLs) (mean size: 15.9 mm) in 73 consecutive women (mean age: 51 years) detected at US were randomly and independently assessed according to the BI-RADS US lexicon, without and with S-Detect, by five independent reviewers. US-guided core-biopsy and 24-month follow-up were considered as standard of reference. Kappa statistics were calculated to assess inter-operator agreement, between the baseline and after S-Detect evaluation. Agreement was graded as poor (≤ 0.20), moderate (0.21-0.40), fair (0.41-0.60), good (0.61-0.80), or very good (0.81-1.00).
results33/73 (45.2%) FBLs were malignant and 40/73 (54.8%) FBLs were benign. A statistically significant improvement of inter-reader agreement from fair to good with the use of S-Detect was observed for shape (from 0.421 to 0.612) and orientation (from 0.417 to 0.7) (p < 0.0001) and from moderate to fair for margin (from 0.204 to 0.482) and posterior features (from 0.286 to 0.522) (p < 0.0001). At baseline analysis isoechoic (0.0485) and heterogeneous (0.1978) echo pattern, microlobulated (0.1161) angular (0.1204) and spiculated (0.1692) margins and combined pattern (0.1549) for posterior features showed the worst agreement rate (poor). After S-Detect evaluation, all variables but isoechoic pattern showed an agreement class upgrade with a statistically significant improvement of inter-reader agreement (p < 0.0001).
conclusionsS-Detect significantly improved inter-reader agreement in the assessment of FBLs according to the BI-RADS US lexicon but evaluation of margin and echo pattern needs to be further improved, particularly isoechoic pattern.
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