ABSTRACT
OBJECTIVES: To demonstrate that radiologists, with the help of artificial intelligence (AI), are able to better classify screening mammograms into the correct breast imaging reporting and data system (BI-RADS) category, and as a secondary objective, to explore the impact of AI on cancer detection and mammogram interpretation time. METHODS: A multi-reader, multi-case study with cross-over design, was performed, including 314 mammograms. Twelve radiologists interpreted the examinations in two sessions delayed by a 4 weeks wash-out period with and without AI support. For each breast of each mammogram, they had to mark the most suspicious lesion (if any) and assign it with a forced BI-RADS category and a level of suspicion or "continuous BI-RADS 100". Cohen's kappa correlation coefficient evaluating the inter-observer agreement for BI-RADS category per breast, and the area under the receiver operating characteristic curve (AUC), were used as metrics and analyzed. RESULTS: On average, the quadratic kappa coefficient increased significantly when using AI for all readers [κ = 0.549, 95% CI (0.528-0.571) without AI and κ = 0.626, 95% CI (0.607-0.6455) with AI]. AUC was significantly improved when using AI (0.74 vs 0.77, p = 0.004). Reading time was not significantly affected for all readers (106 s without AI and vs 102 s with AI; p = 0.754). CONCLUSIONS: When using AI, radiologists were able to better assign mammograms with the correct BI-RADS category without slowing down the interpretation time.
Subject(s)
Breast Neoplasms , Female , Humans , Artificial Intelligence , Breast Neoplasms/diagnostic imaging , Breast Neoplasms/pathology , Early Detection of Cancer , Mammography/methods , Observer Variation , Cross-Over StudiesABSTRACT
Magnetic resonance imaging is the optimal modality for pelvic imaging. It is based on T2-weighted magnetic resonance (MR) sequences allowing uterine and vaginal cavity assessment as well as rectal evaluation. Anatomical depiction of these structures may benefit from distension, and conditions either developing inside the lumen of cavities or coming from the outside may then be better delineated and localized. The need for distension, either rectal or vaginal, and the way to conduct it are matters of debate, depending on indication for which the MR examination is being conducted. In this review, we discuss advantages and potential drawbacks of this technique, based on literature and our experience, in the evaluation of various gynecological and rectal diseases.