European Society of Breast Imaging
ESR Essentials: artificial intelligence in breast imaging-practice recommendations by the European Society of Breast Imaging
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European Society of Breast Imaging
Contenu en anglais
Osler répond à partir de cette bibliothèque et cite la recommandation derrière chaque affirmation.
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.
Publiée par European radiology, 2026. Le PDF est présenté tel que publié et reste l’œuvre de ses auteurs et de son éditeur ; l’original se trouve à la source indiquée ici. Les ayants droit peuvent nous demander de retirer un fichier à l’adresse info@prognia.nl.
Prognia résume cette recommandation à des fins de consultation et d’enseignement. Il ne s’agit pas d’un avis médical. Vérifiez toujours la recommandation officielle et les protocoles locaux en vigueur avant de l’appliquer.
