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Patient-Specific Depth-Limiting 3D-Printed Guide for Sternal Wedge Osteotomy: Design, Preclinical Validation, and Single-Case Feasibility

2026 · Journal of Chest Wall Surgery · 0 citations

Abstract

We evaluated the technical feasibility of a patient-specific, depth-limiting 3D-printed guide intended to support standardized sternal wedge osteotomy by facilitating controlled angulation and proportional depth limitation (osteotomy depth not exceeding two-thirds of total sternal thickness, preserving the posterior one-third). Chest computed tomography data were segmented to generate three-dimensional sternal models, virtually define the wedge angle (≈30°), and design a guide with anatomy-conforming seating, predefined saw slots, a proportional depth stop, and fenestrations for visualization and suction. Preclinical evaluation was performed in five 3D-printed models, with three additional freehand simulations conducted for internal technical comparison. Guide-assisted osteotomies appeared to demonstrate lower mean angular deviation from the digital plan (2.1 ± 0.8°) than freehand simulations (11 ± 1.0°). Angle and depth were assessed using optical 3D scanning aligned with the original CAD plan, with excellent interobserver agreement (ICC > 0.90). Clinical feasibility was assessed in a single 35-year-old man undergoing a modified Ravitch procedure. Guide-assisted wedge osteotomy was completed as planned, with preservation of the posterior cortex. Operative time was 56 minutes, estimated blood loss was <50 mL, and length of hospital stay was 2 days. Planned correction was achieved (sternal inclination 42° → 12°) and remained stable at 18 months of follow-up; no complications were observed. In this limited preclinical evaluation and single clinical application, the patient-specific depth-limiting guide appeared technically feasible and allowed planned execution of osteotomy parameters. These findings should be interpreted as proof-of-concept, and larger clinical series are required to further evaluate reproducibility, safety, and generalizability.

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