# 3D Printing Today, AI Tomorrow: Rethinking Apert Syndrome Surgery in Low-Resource Settings

## TL;DR

This case study shows how low-cost 3D printing can help surgeons plan complex craniofacial surgeries in resource-limited areas, with future potential for AI to improve the process.

## Contribution

The first documented use of low-cost 3D printing for presurgical planning in Apert syndrome within a low-resource setting.

## Key findings

- A 3D-printed model enabled better preoperative planning and reduced surgical complications.
- Fused deposition modeling with ABS filament proved effective for cranial model fabrication.
- AI could enhance future models through automated segmentation and reconstruction.

## Abstract

Background/Objectives: This case study presents the first documented use of a low-cost, simulated, patient-specific three-dimensional (3D) printed model to support presurgical planning for an infant with Apert syndrome in a resource-limited setting. The primary objectives are to (1) demonstrate the value of 3D printing as a simulation tool for preoperative planning in low-resource environments and (2) identify opportunities for future AI-enhanced simulation models in craniofacial surgical planning. Methods: High-resolution CT data were segmented using InVesalius 3, with mesh refinement performed in ANSYS SpaceClaim (version 2021). The cranial model was fabricated using fused deposition modeling (FDM) on a Creality Ender-3 printer with Acrylonitrile Butadiene Styrene (ABS) filament. Results: The resulting 3D-printed simulated model enabled the surgical team to assess cranial anatomy, simulate incision placement, and rehearse osteotomies. These steps contributed to a reduction in operative time and fewer complications during surgery. Conclusions: This case demonstrates the value of accessible 3D printing as a simulation tool in surgical planning within low-resource settings. Building on this success, the study highlights potential points for AI integration, such as automated image segmentation and model reconstruction, to increase efficiency and scalability in future 3D-printed simulation models.