Feasibility of automatic screw planning via transformer-based shape completion from RGB-D imaging

Accurate pedicle screw placement (PSP) is essential in spinal fusion surgery. Conventional navigation relies on computed tomography (CT) or fluoroscopy, which involves ionizing radiation and requires an error-prone registration procedure. We propose a pipeline that enables PSP planning directly on vertebral point clouds reconstructed from intraoperative RGB-D scans, using the SurgPointTransformer network. The system detects screw entry and pedicle regions, estimates initial trajectories, and refines them via anatomically constrained optimization. We evaluated our method on nine ex-vivo cadaveric specimens, comparing RGB-D-based planning to a CT-based baseline using both RGB-D reconstructions and ground-truth CT meshes. No significant differences were found in entry-point offset (3.53 ± 1.30 mm vs. 3.90 ± 1.29 mm), pedicle-center offset (1.58 ± 0.58 mm vs. 1.68 ± 0.59 mm), trajectory-angle error (7.31 ± 3.34[Formula: see text] vs. 7.67 ± 3.59[Formula: see text]); all [Formula: see text]. Safety analysis using the Gertzbein-Robbins classification showed 100% radiologically optimal screw placement (grade A) with both methods. PSP planned from RGB-D reconstructions of the exposed dorsal surface alone achieved planning-level accuracy comparable to CT-based planning on the entire vertebral body. Prospective intraoperative validation is required to establish execution accuracy and clinical outcomes.