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Background: The use of 3D-printed anatomical models in medical education is often limited by the high cost of proprietary software, technical complexity, and lack of accessible implementation resources including . These barriers disproportionately affect learners and institutions with limited funding. 

Objective: To develop a publicly accessible, UCLA-hosted website that provides a structured, open-source workflow for creating 3D-printed anatomical models to enhance accessibility and integration of 3D printing in medical education.

Methods: We developed a web-based platform that provides a structured, step-by-step workflow for creating anatomical models using exclusively open-source software and consumer-grade hardware. The resource organizes key stages of the process, including sourcing anatomically accurate models, understanding file formats, performing mesh inspection and modification, preparing models using slicing software, and optimizing printing and post-processing techniques. Content was derived from various sources including the NIH, 3D printing manufacturers’ websites, and blogs from physicians and hobbyists in this space.

Results: An initial review, which evaluated existing guides on 3D-printing in medical education, highlighted the lack of published literature in this space. We were, however, able to find multiple papers studying the use of different polymers (such as resin, silicone, and polylactic acid) as printing material for various organs and tissue types. Current applications of 3D printing in medical education include anatomy instruction, ultrasound training, fracture management, surgical planning, and procedural skills training and simulation. The resulting website translates a complex technical process into a centralized and user-friendly educational tool. It supports self-directed learning and can be integrated into existing curricula, including anatomy education, surgical planning exposure, and procedural skills training. As a supplementary component, a prototype 3D-printed shoulder model derived from HIPAA-compliant MRI data is being developed to demonstrate real-world application of the workflow.

Conclusion: This project demonstrates a novel medical education innovation that leverages digital scholarship and open-source technology to improve access to hands-on learning tools. By reducing financial and technical barriers, the platform provides a scalable model for disseminating practical 3D printing methods and promoting educational equity across institutions.