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Autonomous Needle Navigation in Subretinal Injections via iOCT.
Peiyao Zhang1, Ji Woong Kim1, Peter Gehlbach2
1Department of Mechanical Engineering and the Laboratory for Computational Sensing and Robotics (LCSR), Johns Hopkins University, Baltimore, MD 21211, USA.
IEEE Robotics and Automation Letters
|March 29, 2024
Summary
This study introduces a robot-assisted system for precise subretinal injections, overcoming surgical challenges like hand tremor and depth perception. The autonomous workflow achieved a 100% success rate in phantom and animal models.
Area of Science:
- Ophthalmology
- Robotics
- Medical Imaging
Background:
- Subretinal injection is crucial for treating retinal diseases.
- Surgical challenges include hand tremor, depth perception, and lack of tactile feedback.
- Intraoperative Optical Coherence Tomography (iOCT) provides depth information but precision remains difficult.
Purpose of the Study:
- To develop a robot-assisted workflow for high-precision autonomous needle navigation in subretinal injection.
- To overcome limitations of manual subretinal surgery using advanced robotic and imaging technologies.
Main Methods:
- Online registration between robot and iOCT coordinates.
- Convolutional Neural Network (CNN) for tool-tip localization in iOCT.
- Real-time Model Predictive Control (MPC) for tool-tip planning and tracking.
- Validation using silicone eye phantoms and ex vivo porcine eyes.
Main Results:
- The robot-assisted workflow demonstrated high precision in reaching target depths.
- Mean error and procedure duration were within acceptable ranges.
- A 100% success rate for subretinal injection was achieved.
- Scleral forces were maintained below 15mN during navigation.
Conclusions:
- The proposed robot-assisted workflow enables precise autonomous subretinal needle navigation.
- This technology can significantly improve the safety and efficacy of subretinal injections.
- The system effectively addresses key surgical challenges in treating subretinal diseases.
