Advanced Manufacturing of PLA Surgical Templates for Orbital Floor Geometry: Optimizing Fidelity and Surface Morphology via Variable Layer Height MEX 3D Printing

TL;DR

This paper introduces a new method for creating precise surgical templates for orbital floor reconstruction using 3D printing with variable layer heights.

Contribution

The novel TARMM procedure combines machine learning and variable layer height MEX 3D printing to enhance template fidelity and reduce manufacturing time.

Findings

The TARMM procedure achieves a geometric error within ±0.1 mm for orbital floor templates.

A strong correlation (r = 0.99) between layer height and surface roughness improves template smoothness.

The method reduces surgical preparation time by 30 minutes and offers a cost-effective alternative to photopolymer systems.

Abstract

Precision and Validation: The TARMM procedure ensures orbital floor geometry accuracy up to 0.1 mm, which has been clinically validated across 21 medical cases.

VLH Optimization: Implementing Variable Layer Height (0.07 mm for critical details and 0.3 mm for the base) eliminates stair-step artifacts while maintaining manufacturing speed.

Surface Quality: A strong correlation (r = 0.99) between layer thickness and roughness allows for the smoothness necessary for precise contouring of titanium meshes.

Safety and Cost-Effectiveness: The method provides an economical and non-toxic alternative to expensive systems based on photopolymer resins.

Operational Efficiency: Reducing model preparation time to 30 min enhances operating theatre efficiency and minimizes the risk of intraoperative errors.

Surgical Standard: The TARMM workflow is a scalable solution ready for implementation as a routine standard in maxillofacial surgery.

Precise orbital floor reconstruction requires personalised surgical templates that combine high geometric fidelity with manufacturing efficiency. This study presents and validates the TARMM procedure, developed to optimise the production of polylactide (PLA) templates. A key innovation is the integration of advanced machine learning algorithms (Random Forest) and Mitchell–Netravali interpolation to reduce medical reconstruction artefacts, as well as the implementation of Material Extrusion (MEX) technology with Variable Layer Height (VLH). This strategy minimises the stair-step effect on complex anatomical curvatures while maintaining high process throughput. The results demonstrate that the TARMM procedure ensures a geometric error within ±0.1 mm. A strong linear correlation (r = 0.99) was found between layer height and surface roughness (Sa), indicating that a 0.07 mm layer in critical areas significantly improves template morphology and facilitates the contouring of titanium meshes. The clinical validation across 21 cases confirmed a 30 min reduction in surgical preparation time. The developed method serves as a low-cost, high-precision alternative to photopolymerization technologies, contributing to modern 3D printing applications in maxillofacial surgery.

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