journal article·2026-02-01Open access

Ophthalmic surgical robot for precise retinal puncture and drug delivery

Chunbo Wang, Mengyao Liu, Zhao Li, He Zhang, Qun Wang, Yanhe Zhu, Liqiang Wang, Jie Zhao

Abstract

Abstract Subretinal injection (SI) is recognized as the most effective method for treating retinal degenerative and genetic diseases, enabling targeted delivery of therapeutic agents such as viral vectors or stem cells directly into the subretinal space (SRS). However, this procedure is typically performed under extremely constrained intraocular conditions, characterized by limited visualization, lack of tactile feedback, and the inherent fragility of retinal tissues, significantly increasing the risk of surgical complications and potential vision impairment. To overcome these challenges, an integrated force-sensing microneedle equipped with a flexible joint was developed and integrated into an ophthalmic surgical robotic system. This advanced system provides precise needle-tip pose control and real-time puncture force feedback. Leveraging these capabilities, force-guided autonomous retinal puncture was achieved, ensuring accurate and consistent drug delivery into the SRS. Comparative experiments conducted on live Bama pigs demonstrated the robotic system’s superiority over manual SI techniques, as evidenced by more stable puncture trajectories, smoother insertion velocities, precise insertion depths, and a greater than 90% reduction in average puncture force, despite respiratory and cardiac-induced disturbances, thus significantly enhancing surgical precision and minimizing the risk of iatrogenic retinal injury. Postoperative evaluations further validated that the robotic approach markedly reduced drug reflux into the vitreous cavity, underscoring its reliability and safety for SI.
Source: crossref · Quality: baseline

Research context

OpenAlex topics: Retinal and Macular Surgery · Intraocular Surgery and Lenses · Retinal and Optic Conditions

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

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