ArticleEuropean radiology2022
Breast MRI: does a clinical decision algorithm outweigh reader experience?
Article in European radiology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
3 citing papers in PubMed, 1 synthesis or guideline pooled it, 14 citations in OpenAlex.
- Economic evaluation of breast MRI in screening - a systematic review and basic approach to cost-effectiveness analyses.Frontiers in oncology · 2023Pooled it
- External validation of multiparametric magnetic resonance imaging-based decision rules for characterizing breast lesions and comparison to Kaiser score and breast imaging reporting and data system (BI-RADS) category.Quantitative imaging in medicine and surgery · 2025Article
- Application of the Kaiser score on contrast-enhanced mammography in the differential diagnosis of breast lesions: comparison with breast magnetic resonance imaging.Quantitative imaging in medicine and surgery · 2024Article
Corrections and comments
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Authors and funding
9 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectivesDue to its high sensitivity, DCE MRI of the breast (MRIb) is increasingly used for both screening and assessment purposes. The Kaiser score (KS) is a clinical decision algorithm, which formalizes and guides diagnosis in breast MRI and is expected to compensate for lesser reader experience. The aim was to evaluate the diagnostic performance of untrained residents using the KS compared to off-site radiologists experienced in breast imaging using only MR BI-RADS.
methodsThree off-site, board-certified radiologists, experienced in breast imaging, interpreted MRIb according to the MR BI-RADS scale. The same studies were read by three residents in radiology without prior training in breast imaging using the KS. All readers were blinded to clinical information. Histology was used as the gold standard. Statistical analysis was conducted by comparing the AUC of the ROC curves.
resultsA total of 80 women (median age 52 years) with 93 lesions (32 benign, 61 malignant) were included. The individual within-group performance of the three expert readers (AUC 0.723-0.742) as well as the three residents was equal (AUC 0.842-0.928), p > 0.05, respectively. But, the rating of each resident using the KS significantly outperformed the experts' ratings using the MR BI-RADS scale (p ≤ 0.05).
conclusionThe KS helped residents to achieve better results in reaching correct diagnoses than experienced radiologists empirically assigning MR BI-RADS categories in a clinical "problem solving MRI" setting. These results support that reporting breast MRI benefits more from using a diagnostic algorithm rather than expert experience. KEY POINTS: • Reporting breast MRI benefits more from using a diagnostic algorithm rather than expert experience in a clinical "problem solving MRI" setting. • The Kaiser score, which provides a clinical decision algorithm for structured reporting, helps residents to reach an expert level in breast MRI reporting and to even outperform experienced radiologists using MR BI-RADS without further formal guidance.
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