Contrast Enhanced Mammography (CEM): is Experience Necessary? an Inter and Intra-Reader Agreement Study for Lesion Classification and Breast Density
Medical Imaging 2024 Image Perception, Observer Performance, and Technology Assessment(2024)
Abstract
The aim of this study is to measure reader agreement for i) lesion classification and ii) breast density in Contrast Enhanced Mammography (CEM). Methods: Two experienced and two inexperienced CEM readers reported 60 examinations. Kappa was used to assess inter-reader agreement between experienced and inexperienced readers for lesion classification (benign/malignant) and breast density (dense/non-dense). Weighted kappa was used to assess agreement for BI-RADS categories (1-5) and BI-RADS density (A-D). Intraclass correlation coefficient (ICC) measured agreement for breast density using Visual Analog scale (VAS). Intra-reader agreement for one experienced and one inexperienced reader was measured after a three month interval. Results: Agreement between experienced readers was substantial (κ=0.66) for benign/malignant, and moderate (κ=0.57) for BI-RADS categories. Agreement for inexperienced readers was moderate for benign/malignant and BI-RADS categories (κ=0.52, κ=0.47 respectively). Breast density (dense/non-dense) agreement was almost perfect for experienced readers (κ=0.83) and substantial for BI-RADS (κ=0.70). Inexperienced reader agreement was moderate for dense/non-dense (κ=0.50) and BI-RADS (κ=0.49). ICC for VAS was moderate for experienced (ICC=0.60) and good (ICC=0.84) for inexperienced readers. Intra-reader agreement for benign/malignant classification was almost perfect for both experienced and inexperienced readers respectively (κ=0.83, κ=0.91). Conclusion: Experienced readers showed substantial agreement for lesion classification and almost perfect agreement for breast density. While inexperienced reader agreement was moderate for both lesion classification and breast density, their agreement for VAS was higher than experienced readers, suggesting that CEM may have a short learning curve and that radiologists could potentially be trained for CEM interpretation, which would help its implementation in other clinical practices in Saudi Arabia.
MoreTranslated text
AI Read Science
Must-Reading Tree
Example
![](https://originalfileserver.aminer.cn/sys/aminer/pubs/mrt_preview.jpeg)
Generate MRT to find the research sequence of this paper
Chat Paper
Summary is being generated by the instructions you defined