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BACKGROUND AND OBJECTIVES: Hand-sewn (HS) microsuturing is limited by tremor and fatigue. Robotic systems may improve performance, but quantitative comparisons remain limited. This study evaluates the precision of robot-assisted vs manual suturing during end-to-side microanastomosis. METHODS: Under simulation, microsurgical robot-assisted and HS sutures for end-to-side microanastomosis were performed by a single surgeon. One thousand four hundred and ninety-four total frames were assessed within 4 videos. Each robotic clip was paired with a corresponding HS clip. Tracker software extracted 2-dimensional positional data. Motion trajectories were smoothed using Savitzky-Golay filtering for an ideal suture trajectory. Deviation from an ideal path was quantified using Euclidean distance. Mean and SD of path deviation were calculated. Group comparisons were made as fold-change reductions and standardized effect sizes (Cohen d) to quantify the magnitude of observed differences. RESULTS: Robotic-assisted sutures demonstrated significantly lower mean path deviation and variability than HS sutures, particularly for the dominant (right) hand, with consistently large effect sizes for the right hand (all = 1.2, r = 0.5) and smaller for the left hand (d = 0.36-0.71, r = 0.18-0.33). CONCLUSION: Robotic microsuturing with microsurgical assistant significantly improves path fidelity, particularly in dominant-hand tasks. Manual sutures showed larger deviations between the ideal suture and raw data, supporting robotic integration into cerebrovascular neurosurgery and warranting study in live models.
Gutstadt et al. (Mon,) studied this question.