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.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8137795 | PMC |
http://dx.doi.org/10.1007/s40477-020-00476-5 | DOI Listing |
Eur Radiol
January 2025
Department of Radiology and Nuclear Medicine, Amsterdam University Medical Center, University of Amsterdam, Amsterdam Cardiovascular Sciences, Amsterdam, The Netherlands.
Objectives: The use of deep learning models for quantitative measurements on coronary computed tomography angiography (CCTA) may reduce inter-reader variability and increase efficiency in clinical reporting. This study aimed to investigate the diagnostic performance of a recently updated deep learning model (CorEx-2.0) for quantifying coronary stenosis, compared separately with two expert CCTA readers as references.
View Article and Find Full Text PDFJ Magn Reson Imaging
January 2025
Department of Radiology, Endeavor Health, Evanston, Illinois, USA.
Background: Luminal and hemodynamic evaluations of the cervical arteries inform the diagnosis and management of patients with cervical arterial disease.
Purpose: To demonstrate a 3D nonenhanced quantitative quiescent interval slice-selective (qQISS) magnetic resonance angiographic (MRA) strategy that provides simultaneous hemodynamic and luminal evaluation of the cervical arteries.
Study Type: Prospective.
Korean J Radiol
January 2025
Department of Radiology, Seoul National University Hospital, Seoul, Republic of Korea.
Objective: To prospectively evaluate the effect of accelerated deep learning-based reconstruction (Accel-DL) on improving brain magnetic resonance imaging (MRI) quality and reducing scan time compared to that in conventional MRI.
Materials And Methods: This study included 150 participants (51 male; mean age 57.3 ± 16.
Can Assoc Radiol J
January 2025
Department of Medical Imaging, Sunnybrook Health Sciences Centre, Toronto, ON, Canada.
To determine the feasibility of implementing Ovarian-Adnexal Reporting & Data System (O-RADS) ultrasound (US) for reporting of adnexal masses at our institution, with a specific goal of increasing the use of O-RADS from a baseline of <5% to at least 75% over a 16-month period. A prospective interrupted time series quality improvement study was undertaken over a 16-month period. Plan, do, study, act cycles included: (1) Engagement of interested parties, (2) Targeted educational sessions, (3) Development of reporting templates, (4) Weekly audit-feedback.
View Article and Find Full Text PDFPLoS One
January 2025
Department of Obstetrics and Gynecology, Shinshu University School of Medicine, Matsumoto, Japan.
Purpose: To reveal problems of magnetic resonance imaging (MRI) for diagnosing gastric-type mucin-positive (GMPLs) and gastric-type mucin-negative (GMNLs) cervical lesions.
Methods: We selected 172 patients suspected to have lobular endocervical glandular hyperplasia; their pelvic MR images were categorised into the training (n = 132) and validation (n = 40) groups. The images of the validation group were read twice by three pairs of six readers to reveal the accuracy, area under the curve (AUC), and intraclass correlation coefficient (ICC).
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!