Towards Motion Compensation in Autonomous Robotic Subretinal Injections

TL;DR

This paper introduces a real-time OCT-based motion compensation method for robotic subretinal injections, addressing physiological eye movements to improve precision in delicate retinal therapies.

Contribution

It proposes a novel OCT-based dynamic tracking approach for motion compensation during robotic subretinal injections, a step forward in retinal surgical automation.

Findings

Achieved sub-millimeter tracking accuracy in ex vivo experiments.

Identified challenges in maintaining tool-to-retina distance during injections.

Highlighted the need for improved motion prediction and stability.

Abstract

Exudative (wet) age-related macular degeneration (AMD) is a leading cause of vision loss in older adults, typically treated with intravitreal injections. Emerging therapies, such as subretinal injections of stem cells, gene therapy, small molecules and RPE cells require precise delivery to avoid damaging delicate retinal structures. Robotic systems can potentially offer the necessary precision for these procedures. This paper presents a novel approach for motion compensation in robotic subretinal injections, utilizing real time Optical Coherence Tomography (OCT). The proposed method leverages B$^5$-scans, a rapid acquisition of small-volume OCT data, for dynamic tracking of retinal motion along the Z-axis, compensating for physiological movements such as breathing and heartbeat. Validation experiments on ex vivo porcine eyes revealed challenges in maintaining a consistent tool-to-retina distance, with deviations of up to 200 $\mu m$ for 100 $\mu m$ amplitude motions and over 80 $\mu m$ for 25 $\mu m$ amplitude motions over one minute. Subretinal injections faced additional difficulties, with phase shifts causing the needle to move off-target and inject into the vitreous. These results highlight the need for improved motion prediction and horizontal stability to enhance the accuracy and safety of robotic subretinal procedures.