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Artificial intelligence in interventional radiology: Current concepts and future trends.

Armelle Lesaunier1, Julien Khlaut2, Corentin Dancette2

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Artificial intelligence (AI) is transforming interventional radiology, enhancing preoperative patient selection, perioperative decision-making, and research through advanced deep learning models and artificial health data. This technology promises greater autonomy and improved outcomes in the field.

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Artificial intelligenceData augmentationDeep learningInterventional radiologyRobotics

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Area of Science:

  • Interventional Radiology
  • Artificial Intelligence
  • Medical Imaging

Background:

  • Artificial intelligence (AI) is established in diagnostic radiology and emerging in interventional radiology.
  • AI offers potential to significantly alter daily interventional radiology practices.

Purpose of the Study:

  • To review current and future applications of AI in interventional radiology.
  • To highlight AI's impact on patient management, procedural efficiency, and research.

Main Methods:

  • Review of recent advances in deep learning and foundation models.
  • Exploration of AI applications in preoperative, perioperative, and research settings.
  • Integration of AI with robotic technologies and artificial health data.

Main Results:

  • AI facilitates multimodality management and increased autonomy in preoperative settings.
  • AI assists in real-time image analysis and decision-making, improving efficiency and safety.
  • AI-based data augmentation addresses research challenges and stimulates innovation.

Conclusions:

  • AI is poised to revolutionize interventional radiology by enhancing patient selection, procedural accuracy, and research capabilities.
  • The synergy of AI with robotics points towards increased autonomy in interventions.
  • AI-driven innovations are crucial for the future of interventional radiology.