Artificial intelligence in emergency neuroradiology: Current applications and perspectives

Area of Science:

• Neuroradiology
• Artificial Intelligence
• Medical Imaging

Background:

• Emergency neuroradiology is critical for acute conditions of the brain, head, neck, and spine.
• Artificial intelligence (AI) applications in this field have rapidly advanced.
• AI offers potential for improved diagnostic speed and accuracy.

Purpose of the Study:

• To provide an up-to-date review of AI applications in emergency neuroradiology.
• To analyze machine learning and deep learning in stroke, hemorrhage, and other acute pathologies.
• To discuss practical considerations and future directions for AI in neuroradiology.

Main Methods:

• Narrative review of current literature on AI in emergency neuroradiology.
• Analysis of AI algorithms (machine learning, deep learning) for various acute conditions.
• Inclusion of commercial product examples and discussion of imaging modalities.

Main Results:

• AI shows significant expansion in depth and scope for acute conditions.
• Detailed analysis covers AI in acute ischemic stroke, intracranial hemorrhage, and vascular pathologies.
• Applications in infection, fracture, cord compression, and pediatric imaging are also discussed.

Conclusions:

• AI is substantially impacting emergency neuroradiology diagnostics.
• Clinical need-driven development, pediatric neuroimaging focus, and real-world performance analysis are crucial.
• AI holds promise for enhancing emergency neuroradiology workflows and patient outcomes.