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迈向自主机器人视网膜下注射中的运动补偿

Towards Motion Compensation in Autonomous Robotic Subretinal Injections.

作者信息

Arikan Demir, Esfandiari Mojtaba, Zhang Peiyao, Sommersperger Michael, Dehghani Shervin, Taylor Russell H, Ali Nasseri M, Gehlbach Peter, Navab Nassir, Iordachita Iulian

机构信息

D. Arikan, M. Sommersperger, S. Dehghani, M. Ali Nasseri are with Department of Computer Science, Technische Universität München, Munich 85748 Germany.

D. Arikan, M. Esfandiari, P. Zhang, R. H. Taylor and I. Iordachita are with the Laboratory for Computational Sensing and Robotics, Johns Hopkins University, Baltimore, MD, USA.

出版信息

Int Symp Med Robot. 2025 May;2025:66-72. doi: 10.1109/ismr67322.2025.11025990. Epub 2025 Jun 13.

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-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 porcine eyes revealed challenges in maintaining a consistent tool-to-retina distance, with deviations of up to 200 μm for 100 μm amplitude motions and over 80 μm for 25 μm 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.

摘要

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,通常通过玻璃体内注射进行治疗。新兴疗法,如视网膜下注射干细胞、基因治疗、小分子和视网膜色素上皮(RPE)细胞,需要精确递送以避免损伤脆弱的视网膜结构。机器人系统有可能为这些手术提供所需的精度。本文提出了一种利用实时光学相干断层扫描(OCT)在机器人视网膜下注射中进行运动补偿的新方法。所提出的方法利用B扫描(一种快速采集小体积OCT数据的方法)来动态跟踪视网膜沿Z轴的运动,补偿诸如呼吸和心跳等生理运动。在猪眼上进行的验证实验表明,在保持工具与视网膜的距离一致方面存在挑战,对于100μm幅度的运动,偏差高达200μm,对于25μm幅度的运动,在一分钟内偏差超过80μm。视网膜下注射面临额外的困难,相移会导致针头偏离目标并注入玻璃体。这些结果凸显了改进运动预测和水平稳定性以提高机器人视网膜下手术的准确性和安全性的必要性。

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