Pre-Surgical Planner for Robot-Assisted Vitreoretinal Surgery: Integrating Eye Posture, Robot Position and Insertion Point

TL;DR

The paper introduces a preoperative planning framework to maximize the visible and accessible workspace for robot-assisted vitreoretinal surgery by jointly optimizing eye posture, trocar insertion, and robot configuration. It converts surgeon-defined 2D targets into 3D positions and uses a sequence of Functions to estimate eye/trocar pose, optimize gaze, select trocars, and compute target angles; the approach is validated on both 3D-printed and silicon phantoms, showing final workflow errors in the sub-degrees and millimeters range. Key contributions include a formal accessibility metric, a strategy to expand the visible-accessible area, and an end-to-end workflow integrating 2D-3D reconstruction, 6D pose estimation, and optimization steps. The results demonstrate the feasibility of preoperative planning to adapt to patient-specific anatomy and target locations, while thoroughly analyzing error sources to guide future improvements in eye pose detection, trocar alignment, and AR-assisted guidance for clinical translation.

Abstract

Several robotic frameworks have been recently developed to assist ophthalmic surgeons in performing complex vitreoretinal procedures such as subretinal injection of advanced therapeutics. These surgical robots show promising capabilities; however, most of them have to limit their working volume to achieve maximum accuracy. Moreover, the visible area seen through the surgical microscope is limited and solely depends on the eye posture. If the eye posture, trocar position, and robot configuration are not correctly arranged, the instrument may not reach the target position, and the preparation will have to be redone. Therefore, this paper proposes the optimization framework of the eye tilting and the robot positioning to reach various target areas for different patients. Our method was validated with an adjustable phantom eye model, and the error of this workflow was 0.13 +/- 1.65 deg (rotational joint around Y axis), -1.40 +/- 1.13 deg (around X axis), and 1.80 +/- 1.51 mm (depth, Z). The potential error sources are also analyzed in the discussion section.

Figures (9)

• Figure 1: Overview of the surgical planner. (a)-(c) in optimization shows the strategy to expand the accessible area.
• Figure 2: (a) shows the whole view of the robot. (b) shows the kinematic structure of the 5-DoF surgical robot.
• Figure 3: 2D-3D conversion. (a)Diagnostic imagefundusimage. The surgeon defines the target. (b) The polar coordinate of the target is obtained from (a). (c) Schematic diagram of the optical and the visual axis.
• Figure 4: Function3. Optimization of the eye posture. It shows the the shift of the field of view (FoV). When the eyeball tilted $\theta_{\rm{tilt}}$, the FoV shifted $-2\theta_{\rm{tilt}}$ from the posterior pole.
• Figure 5: Trocar selection and initial tilting angle. (a) 3D model of the eyeball with trocar and trocar after tilting. (b) Trocar selection. The closest trocar along the X-axis to the center of the target is selected. (c) Movement of the trocar and the target by the eye rotation. (d) Schematic diagram of $\vb{v}_{\rm{trocar2target}}$. $\vb{v}_{\rm{trocar2target}}'$ is the projected vector of $\vb{v}_{\rm{trocar2target}}$ into the YZ plane.