机器人辅助眼内囊膜清洗，实现高精度实时可视化与无损操作
Safe Robotic Capsule Cleaning with Integrated Transpupillary and Intraocular Optical Coherence Tomography
- 集成眼内与经瞳孔OCT探头，实现囊膜全域实时成像
- 在猪眼实验中完成无损伤清洁，模型误差显著降低
- 适合眼科手术机器人研发与微创治疗场景
白内障术后继发性白内障是常见视力丧失原因，由残留晶状体材料在囊膜上增生所致。囊膜清洗是一种潜在治疗方法，需精准可视化囊膜并精细操控器械。本文提出一种机器人系统，将标准经瞳孔和眼内光学相干断层扫描探头集成于手术器械，实现囊膜赤道区域的可视化及工具-组织距离实时反馈。利用机器人高精度，系统可完成瞳孔区与赤道区的完整囊膜建模，并实现折射率与光纤偏移的原位校准，克服了当前获取精确囊膜模型的挑战。通过五次眼模型试验验证，所构建囊膜模型的均方根误差降低；在三个离体猪眼中实施清洗策略，未造成组织损伤。
原文摘要 · Abstract (English)
Secondary cataract is one of the most common complications of vision loss due to the proliferation of residual lens materials that naturally grow on the lens capsule after cataract surgery. A potential treatment is capsule cleaning, a surgical procedure that requires enhanced visualization of the entire capsule and tool manipulation on the thin membrane. This article presents a robotic system capable of performing the capsule cleaning procedure by integrating a standard transpupillary and an intraocular optical coherence tomography probe on a surgical instrument for equatorial capsule visualization and real-time tool-to-tissue distance feedback. Using robot precision, the developed system enables complete capsule mapping in the pupillary and equatorial regions with in-situ calibration of refractive index and fiber offset, which are still current challenges in obtaining an accurate capsule model. To demonstrate effectiveness, the capsule mapping strategy was validated through five experimental trials on an eye phantom that showed reduced root-mean-square errors in the constructed capsule model, while the cleaning strategy was performed in three ex-vivo pig eyes without tissue damage.
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