ArticleJournal of robotic surgery2023
iOCT-guided simulated subretinal injections: a comparison between manual and robot-assisted techniques in an ex-vivo porcine model.
Article in Journal of robotic surgery, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 2 of them syntheses that pooled it.
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Who cites it
11 citing papers in PubMed, 2 syntheses or guidelines pooled it, 17 citations in OpenAlex.
- Next-gen vision: a systematic review on robotics transforming ophthalmic surgery.Journal of robotic surgery · 2025Pooled it
- Sharper vision, steady hands: can robots improve subretinal drug delivery? Systematic review.Journal of robotic surgery · 2024Pooled it
- SS-OCT-guided dual-arm master-slave robotic system for in vivo subretinal injection in porcine eyes.Journal of robotic surgery · 2026Article
- Robot-assisted ophthalmic surgery: research trends, collaboration networks, and emerging clinical frontiers.Journal of robotic surgery · 2026Review
- Bimanual Manipulation of Steady-Hand Eye Robots with Adaptive Sclera Force Control: Cooperative vs. Teleoperation Strategies.IEEE transactions on human-machine systems · 2025Article
- Surgical Approaches to Retinal Gene Therapy: 2025 Update.Bioengineering (Basel, Switzerland) · 2025Review
- The impact of intraoperative optical coherence tomography on cognitive load in virtual reality vitreoretinal surgery training.Scientific reports · 2025Article
- A novel robot-assisted subretinal injection system: preliminary validation in ex vivo porcine eyes.Journal of robotic surgery · 2025Article
- Head-mounted surgical robots are an enabling technology for subretinal injections.Science robotics · 2025Article
- Optimizing Subretinal Bleb Formation for Visual Streak Involvement in a Porcine Model for Retinal Gene Therapy.Investigative ophthalmology & visual science · 2024Article
- Autonomous Needle Navigation in Subretinal Injections via iOCT.IEEE robotics and automation letters · 2024Article
Corrections and comments
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Authors and funding
9 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The purpose of this study is to compare robot-assisted and manual subretinal injections in terms of successful subretinal blistering, reflux incidences and damage of the retinal pigment epithelium (RPE). Subretinal injection was simulated on 84 ex-vivo porcine eyes with half of the interventions being carried out manually and the other half by controlling a custom-built robot in a master-slave fashion. After pars plana vitrectomy (PPV), the retinal target spot was determined under a LUMERA 700 microscope with microscope-integrated intraoperative optical coherence tomography (iOCT) RESCAN 700 (Carl Zeiss Meditec, Germany). For injection, a 1 ml syringe filled with perfluorocarbon liquid (PFCL) was tipped with a 40-gauge metal cannula (Incyto Co., Ltd., South Korea). In one set of trials, the needle was attached to the robot's end joint and maneuvered robotically to the retinal target site. In another set of trials, approaching the retina was performed manually. Intraretinal cannula-tip depth was monitored continuously via iOCT. At sufficient depth, PFCL was injected into the subretinal space. iOCT images and fundus video recordings were used to evaluate the surgical outcome. Robotic injections showed more often successful subretinal blistering (73.7% vs. 61.8%, p > 0.05) and a significantly lower incidence of reflux (23.7% vs. 58.8%, p < 0.01). Although larger tip depths were achieved in successful manual trials, RPE penetration occurred in 10.5% of robotic but in 26.5% of manual cases (p > 0.05). In conclusion, significantly less reflux incidences were achieved with the use of a robot. Furthermore, RPE penetrations occurred less and successful blistering more frequently when performing robotic surgery.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.