Evidenzbasierte und strukturierte Diagnostik in der MR-Mammografie anhand des Kaiser-Score
Baltzer PAT, Krug KB, Dietzel M (2023)
Publication Type: Journal article
Publication year: 2023
Journal
Book Volume: 44
Pages Range: 134-146
Journal Issue: 2
DOI: 10.1055/a-2013-9794
Abstract
Background Breast MRI is the most sensitive method for the detection of breast cancer and is an integral part of modern breast imaging. On the other hand, interpretation of breast MRI exams is considered challenging due to the complexity of the available information. Clinical decision rules that combine diagnostic criteria in an algorithm can help the radiologist to read breast MRI by supporting objective and largely experience-independent diagnosis. Method Narrative review. In this article, the Kaiser Score (KS) as a clinical decision rule for breast MRI is introduced, its diagnostic criteria are defined, and strategies for clinical decision making using the KS are explained and discussed. Results The KS is based on machine learning and has been independently validated by international research. It is largely independent of the examination technique that is used. It allows objective differentiation between benign and malignant contrast-enhancing breast MRI findings using diagnostic BI-RADS criteria taken from T2w and dynamic contrast-enhanced T1w images. A flowchart guides the reader in up to three steps to determine a score corresponding to the probability of malignancy that can be used to assign a BI-RADS category. Individual decision making takes the clinical context into account and is illustrated by typical scenarios. Key Points: The KS as an evidence-based decision rule to objectively distinguish benign from malignant breast lesions is based on information contained in T2w und dynamic contrast-enhanced T1w sequences and is largely independent of specific examination protocols. The KS diagnostic criteria are in line with the MRI BI-RADS lexicon. We focused on defining a default category to be applied in the case of equivocal imaging criteria. The KS reflects increasing probabilities of malignancy and, together with the clinical context, assists individual decision making. Citation Format Baltzer PA, Krug KB, Dietzel M. Evidence-Based and Structured Diagnosis in Breast MRI using the Kaiser Score. Fortschr Röntgenstr 2022; 194: 1216-1228.
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Involved external institutions
Austria (AT)
Germany (DE)How to cite
APA:
Baltzer, P.A.T., Krug, K.B., & Dietzel, M. (2023). Evidenzbasierte und strukturierte Diagnostik in der MR-Mammografie anhand des Kaiser-Score. TumorDiagnostik & Therapie, 44(2), 134-146. https://dx.doi.org/10.1055/a-2013-9794
MLA:
Baltzer, Pascal Andreas Thomas, Kathrin Barbara Krug, and Matthias Dietzel. "Evidenzbasierte und strukturierte Diagnostik in der MR-Mammografie anhand des Kaiser-Score." TumorDiagnostik & Therapie 44.2 (2023): 134-146.
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