Advancing Embodied Intelligence in Robotic-Assisted Endovascular Procedures: A Systematic Review of AI Solutions

Area of Science:

• Medical Robotics
• Artificial Intelligence in Medicine
• Vascular Surgery

Background:

• Endovascular procedures offer significant benefits for vascular disease but face challenges like precision demands, operator fatigue, and radiation exposure.
• Robotic systems are emerging as solutions to overcome these limitations.
• A convergence of clinical needs and AI advancements presents an opportunity for Embodied Intelligence (EI) in endovascular robotics.

Purpose of the Study:

• To systematically review the integration of Embodied Intelligence (EI) into endovascular robotic systems.
• To analyze the challenges and opportunities presented by EI in this field.
• To propose a future roadmap for augmented intelligence in endovascular interventions.

Main Methods:

• Review of current literature on EI, AI, computer vision, and machine learning in endovascular robotics.
• Analysis of data-driven approaches for real-time vessel segmentation, device tracking, and landmark detection.
• Exploration of reinforcement learning and imitation learning for navigation strategies.

Main Results:

• EI enables robots to navigate complex vascular networks and adapt to physiological conditions.
• AI-driven methods facilitate real-time analysis for improved procedural accuracy.
• Challenges include heterogeneous validation standards and the gap between human mimicry and machine capabilities.

Conclusions:

• The future of endovascular robotics lies in augmented intelligence, not full automation.
• Clinicians' roles will evolve to high-level supervision, leveraging EI for enhanced decision-making.
• This approach provides a principled foundation for advancing the field of minimally invasive vascular treatment.