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.

翻译：渗出性（湿性）年龄相关性黄斑变性（AMD）是导致老年人视力丧失的主要原因，通常通过玻璃体内注射进行治疗。新兴疗法，如干细胞、基因疗法、小分子药物和视网膜色素上皮细胞的视网膜下注射，需要精确递送以避免损伤脆弱的视网膜结构。机器人系统有望为这些手术提供必要的精度。本文提出了一种利用实时光学相干断层扫描（OCT）实现机器人视网膜下注射运动补偿的新方法。该方法利用B$^5$扫描（一种小体积OCT数据的快速采集技术）动态跟踪视网膜沿Z轴的运动，以补偿呼吸和心跳等生理运动。在离体猪眼上进行的验证实验揭示了维持工具与视网膜之间恒定距离的挑战：对于100 $\mu m$幅度的运动，一分钟内偏差高达200 $\mu m$；对于25 $\mu m$幅度的运动，偏差超过80 $\mu m$。视网膜下注射面临更多困难，相位偏移导致针头偏离目标并将药物注入玻璃体。这些结果凸显了改进运动预测和水平稳定性对于提高机器人视网膜下手术精度和安全性的必要性。