European Society of Breast Imaging
ESR Essentials: artificial intelligence in breast imaging-practice recommendations by the European Society of Breast Imaging
Inhalt auf Englisch
Deine Seite wird geladen …
Deine Seite wird geladen …
European Society of Breast Imaging
Inhalt auf Englisch
Osler antwortet aus dieser Bibliothek und nennt zu jeder Aussage die Leitlinie dahinter.
Artificial intelligence (AI) can enhance the diagnostic performance of breast cancer imaging and improve workflow optimization, potentially mitigating excessive radiologist workload and suboptimal diagnostic accuracy. AI can also boost imaging capabilities through individual risk prediction, molecular subtyping, and neoadjuvant therapy response predictions. Evidence demonstrates AI's potential across multiple modalities. The most robust data come from mammographic screening, where AI models improve diagnostic accuracy and optimize workflow, but rigorous post-market surveillance is required before any implementation strategy in this field. Commercial tools for digital breast tomosynthesis and ultrasound, potentially able to reduce interpretation time and improve accuracy, are also available, but post-implementation evaluation studies are likewise lacking. Besides basic tools for breast MRI with limited proven clinical benefit, AI applications for other modalities are not yet commercially available. Applications in contrast-enhanced mammography are still in the research stage, especially for radiomics-based molecular subtype classification. Applications of Large Language Models (LLMs) are in their infancy, and there are currently no clinical applications. Consequently, and despite their promise, all commercially available AI tools for breast imaging should currently still be regarded as techniques that, at best, aid radiologists in image evaluation. Their use is therefore optional, and the findings may always be overruled. KEY POINTS: AI systems improve diagnostic accuracy and efficiency of mammography screening, but long-term outcomes data are lacking. Commercial tools for digital breast tomosynthesis and ultrasound are available, but post-implementation evaluation studies are lacking. AI tools for breast imaging should still be regarded as a non-obligatory aid to radiologists for image interpretation.
Veröffentlicht von European radiology, 2026. Das PDF wird so gezeigt, wie es veröffentlicht wurde, und bleibt das Werk seiner Autoren und seines Verlags; das Original findest du bei der hier verlinkten Quelle. Rechteinhaber können uns unter info@prognia.nl bitten, eine Datei zu entfernen.
Prognia fasst diese Leitlinie zum Nachschlagen und Lernen zusammen. Das ist keine medizinische Beratung. Prüfe immer die offizielle Leitlinie und die aktuellen lokalen Standards, bevor du danach handelst.
