S-Detect characterization of focal solid breast lesions: a prospective analysis of inter-reader agreement for US BI-RADS descriptors
- Autori: Bartolotta T.V.; Orlando A.A.M.; Di Vittorio M.L.; Amato F.; Dimarco M.; Matranga D.; Ienzi R.
- Anno di pubblicazione: 2021
- Tipologia: Articolo in rivista
- Parole Chiave: BI-RADS; Breast neoplasms; Computer-assisted diagnosis; Decision-making; Problem-solving; Ultrasonography
- OA Link: http://hdl.handle.net/10447/431813
Abstract
Background: To assess inter-reader agreement for US BI-RADS descriptors using S-Detect: a computer-guided decision-making software assisting in US morphologic analysis. Methods: 73 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). Results: 33/73 (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). Conclusions: S-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.