Abstract

Breast Magnetic Resonance Imaging (MRI) combined with Artificial Intelligence (AI) has emerged as a transformative force in breast cancer diagnostics. This abstract presents an overview of the current advances and future prospects of AI in breast MRI. AI algorithms exhibit remarkable capabilities in lesion detection, quantitative analysis, risk assessment, and treatment response monitoring. Integrating AI into breast MRI enhances accuracy, aids in personalized risk assessment, and facilitates treatment planning. However, challenges persist regarding data standardization, clinical validation, and algorithm interpretability. Future horizons envision predictive analytics, automated reporting, personalized treatment strategies, and global collaboration to establish standards. The integration of AI in breast MRI holds immense promise to revolutionize breast cancer diagnosis, prognosis, and patient care, demanding collaborative efforts to bridge research advancements with clinical practice for optimized outcomes. The rapid development and subsequent implementation of AI into clinical breast MRI has the potential to affect clinical decision-making, guide treatment selection, and improve patient outcomes. The goal of this review is to provide a comprehensive picture of the current status and future perspectives of AI in breast MRI.