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 or RPE cells require precise delivery to avoid damaging delicate retinal structures. Autonomous 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 \textit{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 horizontal 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.
Abstract (translated)
渗出性（湿性）年龄相关性黄斑变性(AMD)是老年人视力丧失的主要原因之一，通常采用玻璃体腔注射治疗。新兴的疗法，如视网膜下干细胞注射、基因治疗、小分子或RPE细胞注射等，则需要精确地输送到目标位置以避免损伤脆弱的视网膜结构。自主机器人系统可能提供这些程序所需的精度。本文提出了一种用于机器人视网膜下注射中运动补偿的新方法，利用实时光学相干断层扫描(OCT)技术。该方法利用B$^{5}$-scan（快速获取小体积OCT数据）对Z轴上的视网膜动态进行跟踪，以补偿呼吸和心跳等生理运动引起的位移。在离体猪眼上的验证实验显示，在一分钟内，对于100微米幅度的运动，保持工具到视网膜距离一致性的偏差可达200微米；而对于25微米幅度的运动，超过80微米的偏差也普遍存在。视网膜下注射还面临额外困难，水平位移导致针头偏离目标区域，注入玻璃体中。这些结果突显了提高运动预测和横向稳定性的必要性，以提升机器人视网膜下程序的准确性和安全性。
URL
https://arxiv.org/abs/2411.18521
