ArticleEuropean radiology2013
A simple and robust classification tree for differentiation between benign and malignant lesions in MR-mammography.
Article in European radiology, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 43 papers, 2 of them syntheses that pooled it.
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Who cites it
43 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Can structured integration of BI-RADS criteria by a clinical decision rule reduce the number of unnecessary biopsies in BI-RADS 4 lesions? A systematic review and meta-analysis.European radiology · 2025Pooled it
- Diagnostic Performance of Artificial Intelligence in Detection of Hepatocellular Carcinoma: A Meta-analysis.Journal of imaging informatics in medicine · 2024Pooled it
- Diagnostic performance of Kaiser score, ADC, and their combination for BI-RADS 4 breast lesions: subgroup and misclassification analysis.Frontiers in oncology · 2026Article
- The role of the Kaiser score system in uncertain malignant potential (B3) breast lesions: a pilot study.Diagnostic and interventional radiology (Ankara, Turkey) · 2025Article
- Relationships Between Breast Edema and Axillary Lymph Node Metastasis in Breast Cancer.Diagnostics (Basel, Switzerland) · 2025Article
- 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
- Breast lesions on MRI in mass and non-mass enhancement: Kaiser score and modified Kaiser score + for readers of variable experience.European radiology · 2025Article
- Reliability of Kaiser Score in Assessing Additional Breast Lesions Identified on Staging MRI in Patients with Breast Cancer.Diagnostics (Basel, Switzerland) · 2024Article
- 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
- Quantitative evaluation of Kaiser score in diagnosing breast dynamic contrast-enhanced magnetic resonance imaging for patients with high-grade background parenchymal enhancement.Quantitative imaging in medicine and surgery · 2023Article
- Combination of ultrafast dynamic contrast-enhanced MRI-based radiomics and artificial neural network in assessing BI-RADS 4 breast lesions: Potential to avoid unnecessary biopsies.Frontiers in oncology · 2023Article
- Radiomics analysis of amide proton transfer-weighted and structural MR images for treatment response assessment in malignant gliomas.NMR in biomedicine · 2023Article
- Assessment of breast lesions by the Kaiser score for differential diagnosis on MRI: the added value of ADC and machine learning modeling.European radiology · 2022Article
- Breast MRI: does a clinical decision algorithm outweigh reader experience?European radiology · 2022Article
- Can DWI provide additional value to Kaiser score in evaluation of breast lesions.European radiology · 2022Article
- Application of the Kaiser score by MRI in patients with breast lesions by ultrasound and mammography.Diagnostic and interventional radiology (Ankara, Turkey) · 2022Article
- A simplified scoring protocol to improve diagnostic accuracy with the breast imaging reporting and data system in breast magnetic resonance imaging.Quantitative imaging in medicine and surgery · 2022Article
- Evaluation of Ultrasound Elastography Combined With Chi-Square Automatic Interactive Detector in Reducing Unnecessary Fine-Needle Aspiration on TIRADS 4 Thyroid Nodules.Frontiers in oncology · 2022Article
- Evaluation of the differentiation of benign and malignant breast lesions using synthetic relaxometry and the Kaiser score.Frontiers in oncology · 2022Article
- Magnetic resonance imaging in diagnosis of indeterminate breast (BIRADS 3 & 4A) in a general population.Insights into imaging · 2021Article
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3 authors.
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Abstract
objectivesIn the face of multiple available diagnostic criteria in MR-mammography (MRM), a practical algorithm for lesion classification is needed. Such an algorithm should be as simple as possible and include only important independent lesion features to differentiate benign from malignant lesions. This investigation aimed to develop a simple classification tree for differential diagnosis in MRM.
methodsA total of 1,084 lesions in standardised MRM with subsequent histological verification (648 malignant, 436 benign) were investigated. Seventeen lesion criteria were assessed by 2 readers in consensus. Classification analysis was performed using the chi-squared automatic interaction detection (CHAID) method. Results include the probability for malignancy for every descriptor combination in the classification tree.
resultsA classification tree incorporating 5 lesion descriptors with a depth of 3 ramifications (1, root sign; 2, delayed enhancement pattern; 3, border, internal enhancement and oedema) was calculated. Of all 1,084 lesions, 262 (40.4 %) and 106 (24.3 %) could be classified as malignant and benign with an accuracy above 95 %, respectively. Overall diagnostic accuracy was 88.4 %.
conclusionsThe classification algorithm reduced the number of categorical descriptors from 17 to 5 (29.4 %), resulting in a high classification accuracy. More than one third of all lesions could be classified with accuracy above 95 %. KEY POINTS: • A practical algorithm has been developed to classify lesions found in MR-mammography. • A simple decision tree consisting of five criteria reaches high accuracy of 88.4 %. • Unique to this approach, each classification is associated with a diagnostic certainty. • Diagnostic certainty of greater than 95 % is achieved in 34 % of all cases.
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