Feasibility Of Establishing A Low-cost 3d Printing Laboratory In A Low Resource Setting

Background: 3D printing has demonstrated transformative potential in surgical practice, offering applications in surgical planning, training, and patient education. Although this technology is being adopted widely in many high-income countries, high costs and infrastructure requirements remain barriers to widespread adoption in low-resource settings. This study assessed the feasibility of developing an affordable, in-house 3D printing laboratory tailored for such environments. Methods: A mixed-methods approach was used. First a nationwide survey of 70 surgeons working in low-resource hospitals in Türkiye was deployed to assess the demand for 3D printing technologies. Then, an affordable 3D printer and necessary printing materials were procured. Four different anatomical models were chosen for the study purposes. A 3D printing workflow using freely available open-source software was developed. Anonymized patient Computerized Tomography (CT) images were used as input data. Production time and cost analyses were conducted, and surgeons reviewed the models using a validated acceptability questionnaire. Finally, a business case was developed to assess integration within a low-resource setting. Results: Of the survey participants, 85.7% expressed willingness to use 3D printing technologies in surgical practice if available. The total costs per model ranged between $2 and $5 USD including material procurement, personal hourly rates and maintenance costs. Costs were significantly lower than commercially available alternatives. Total 3D printing workflow time ranged from 6 to 25 hours demonstrating feasibility within clinical timelines. Surgeons rated the models as highly acceptable for surgical planning. The business case demonstrated cost-effectiveness compared to outsourcing the services, supporting long-term sustainability. Conclusion: Creating an in-house 3D printing laboratory using open-source software and low-cost hardware is feasible in low-resource settings. Future work should focus on refining anatomical accuracy, expanding applications, and conducting cost-benefit analyses at scale. Disclosures: This work was conducted as part of the MSc study of Egehan Salepci at the University of Oxford.