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Automated Retinal Vein Cannulation on Silicone Phantoms Using Optical-Coherence-Tomography-Guided Robotic
Matthew J Gerber1, Jean-Pierre Hubschman2, Tsu-Chin Tsao1
1Mechanical and Aerospace Engineering Department, University of California, Los Angeles, CA, 90095 USA.
IEEE/ASME Transactions on Mechatronics : a Joint Publication of the IEEE Industrial Electronics Society and the ASME Dynamic Systems and Control Division
|May 9, 2022
Summary
A novel robotic system precisely performs automated retinal vein cannulation, a procedure to treat vision loss from retinal vein occlusion. This image-guided technology shows high accuracy and success in phantom trials.
Area of Science:
- Ophthalmology
- Medical Robotics
- Biomedical Engineering
Background:
- Retinal vein occlusion (RVO) is a leading cause of vision impairment.
- Current treatments for RVO may be limited, necessitating innovative approaches.
- Retinal vein cannulation offers a potential therapeutic strategy for RVO.
Purpose of the Study:
- To develop and evaluate an image-guided robotic system for automated retinal vein cannulation.
- To assess the precision and success rate of automated cannulation in a phantom model.
Main Methods:
- An image-guided robotic system was developed, integrating optical coherence tomography (OCT) and a camera for real-time visual feedback.
- The system was designed to perform automated cannulation on silicone retinal vein phantoms.
- Automated targeting and infusion into the vascular lumen were key procedural steps.
Main Results:
- The robotic system achieved precise targeting of vein phantoms within 20 μm.
- Automated cannulation and infusion of the vascular lumen were successfully performed.
- Across 30 experimental trials, the system demonstrated a 100% success rate with no failures.
Conclusions:
- The developed image-guided robotic system is capable of precise and automated retinal vein cannulation.
- This technology holds promise for improving the treatment of retinal vein occlusion.
- Further research may explore clinical applications of this robotic system for RVO treatment.
