The Role of Artificial Intelligence in Acute Stroke Imaging: Current Status and Future Directions

Abstract Acute stroke imaging is paramount for quick diagnostic decisions using imaging modalities, including computerized tomography and magnetic resonance imaging. These modalities provide valuable information to determine the disease etiology and course of action. “Time is brain,” and as such, there are unique challenges regarding acute stroke imaging, including acute decision making, limited resource availability, and compromised image quality. Artificial intelligence (AI) tools may provide support for acute stroke imaging in clinical care settings and have the potential to mitigate many of these challenges. This paper investigates the role of AI in acute stroke imaging in research and industry, including reviewing 39 papers published between 2022 and 2025 that investigated the development and application of tools specific to interventional radiology and stroke and examined their tools' efficacy and the studies' consideration of data privacy, reproducibility, and practical usability. We also investigated four commercially available AI tools available for clinical use, focusing on their primary objectives, strengths, and limitations. We found that while AI tools demonstrate the potential for improving time-to-treatment and diagnostic accuracy, there are key limitations related to low reproducibility, the development of impractical tools, and minimal documentation about AI development and employment.