Retinal Vein Occlusion (RVO) is a blinding disease caused by one or more occluded retinal veins. Current treatment methods only focus on symptom mitigation rather than targeting a solution for the root cause of the disorder. Retinal vein cannulation is an experimental eye surgical procedure which could potentially cure RVO. Its goal is to dissolve the occlusion by injecting an anticoagulant directly into the blocked vein. Given the scale and the fragility of retinal veins on one end and surgeons' limited positioning precision on the other, performing this procedure manually is considered to be too risky. The authors have been developing robotic devices and instruments to assist surgeons in performing this therapy in a safe and successful manner. This work reports on the clinical translation of the technology, resulting in the world-first in-human robot-assisted retinal vein cannulation. Four RVO patients have been treated with the technology in the context of a phase I clinical trial. The results show that it is technically feasible to safely inject an anticoagulant into a [Formula: see text]-thick retinal vein of an RVO patient for a period of 10 min with the aid of the presented robotic technology and instrumentation.

Retinal Vein Occlusion is a common retinal vascular disorder which can cause severe loss of vision. Retinal vein cannulation followed by injection of an anti-coagulant into the affected vein is a promising treatment. However, given the scale and fragility of the surgical workfield, this procedure is considered too high-risk to perform manually. A first successful robot-assisted procedure has been demonstrated. Even though successful, the procedure remains extremely challenging. This paper aims at providing a solution for the limited perception of instrument-tissue interaction forces as well as depth estimation during retinal vein cannulation. The development of a novel combined force and distance sensing cannulation needle relying on Fiber Bragg grating (FBG) and Optical Coherence Tomography (OCT) A-scan technology is reported. The design, the manufacturing process, the calibration method, and the experimental characterization of the produced sensor are discussed. The functionality of the combined sensing modalities and the real-time distance estimation algorithm are validated respectively on in-vitro and ex-vivo models.

The results demonstrate the feasibility of deploying a combined sensing instrument in an in vivo setting. The performed study provides a foundation for further work on real-time local modelling of the surgical scene. This paper provides initial insights; however, additional processing remains necessary.

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This work reports on the synthesis of a parallel Remote Center of Motion (RCM) mechanism, and an optimized design for the use-case of robot-assisted vitreoretinal surgery. A 2-DoF planar RCM mechanism is proposed and synthesised as part of a 4-DoF RCM mechanism. The proposed design substantially reduces the occupied volume at the end-effector. This solves a major problem present in related state-of-the-art, which poses limitations on sterile end-effector design and surgical instrument compatibility. Subsequently, an optimal design algorithm is proposed and implemented for the given use-case. The workspace is determined within mechanism constraints, after which performance parameters such as workspace coverage, potential energy, manipulability, reflected stiffness are determined for specific areas of interest within a desired workspace. Subsequently, these parameters are combined in a score function identifying an optimal kinematic design. When compared with the closely-related prior art, the resulting design shows improvements in relevant workspace coverage, reduced gravity compensation effort, and more isotropic manipulability. Overall reflected stiffness is reduced and should be taken into account in future design phases. Future work includes the integration of the kinematic design into a detailed conceptual design and a first prototype development.

The developed bio-impedance sensor has shown great promise to help in avoiding double punctures when cannulating retinal veins. Compared to other puncture detection methods, the proposed sensor is simple and therefore potentially more affordable. Future research will include validation in an in vivo situation involving vitreoretinal surgeons.

Purpose To evaluate the safety and feasibility of robot‐assisted retinal vein cannulation with Ocriplasmin infusion for central retinal vein occlusion. Methods Prospective phase I trial including four patients suffering from central retinal vein occlusion (CRVO). Diagnosis was confirmed by preoperative fluo‐angiography and followed by a standard three‐port pars plana vitrectomy. Afterwards, a custom‐built microneedle was inserted into a branch retinal vein with robotic assistance and infusion of Ocriplasmin started. Primary outcomes were the occurrence of intra‐operative complications and success of cannulation. Secondary outcomes were change in visual acuity, central macular thickness (CMT) and venous filling times (VFT) during fluo‐angiography two weeks after the intervention. Results Cannulation with infusion of ocriplasmin was successful in all four eyes with a mean total infusion time of 355 ± 204 seconds (range 120–600 seconds). Best corrected visual acuity (BCVA) remained counting fingers (CF) in case 3 and 4, increased in case 1 from CF to 0.9LogMAR and decreased in case 2 from 0.4 to 1.3 LogMAR. CMT and VFT both showed a trend towards significant decrease comparing preoperative measurements with two weeks postintervention (1061 ± 541 μm versus 477 ± 376 μm, p = 0.068) and 24 ll 4 seconds versus 15 ± 1 seconds, p = 0.068, respectively). In one eye a needle tip broke and could be removed with an endoforceps. There were no other intervention‐related complications. Conclusion Robot‐assisted retinal vein cannulation is feasible and safe. Local intravenous infusion with Ocriplasmin led to an improved retinal circulation.

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