Digital Workflow for 3D-Printed Patient-Specific Radiotherapy Masks

Personalized medicine increasingly leverages additive manufacturing (AM) to bridge digital imaging and physical fabrication. In radiation oncology, patient-specific immobilization masks are essential for maintaining positioning accuracy and reproducibility during treatment. However, conventional mask fabrication involves manual molding and additional patient visits, which can lead to treatment delays and increased patient discomfort. This project introduces a fully digital, end-to-end AM workflow that transforms medical imaging directly into customized radiotherapy masks, reducing patient burden and accelerating clinical implementation.
Computed tomography (CT) or magnetic resonance (MR) imaging data were segmented using an AI-assisted workflow to generate a 3D surface model of the patient’s head. This digital head geometry served as the reference for designing the customized immobilization mask. To reproduce the treatment environment, a 3D scanner captured the geometry of the headrest and immobilization setup. A physics-based cloth-deformation algorithm then simulated the thermoforming of thermoplastic material over the CT/MR-derived head surface and the scanned headrest, enabling accurate prediction of mask fit, pressure distribution, and deformation before fabrication.
Fabrication was performed using fused-filament fabrication (FFF) on a Prusa XL printer with PLA and thermoplastic polyurethane (TPU) to achieve an optimal balance of rigidity, flexibility, and anatomical conformity. CT-based surface deviation mapping demonstrated sub-millimeter geometric accuracy ( < 0.5 mm) between the printed and simulated masks. Volunteer testing confirmed excellent immobilization stability, fit precision, and comfort, with all results meeting clinical tolerance criteria.
The customized 3D-printed mask was produced for approximately $20—compared with about $200 for conventional thermoplastic masks, excluding additional costs associated with office visits and technician labor—achieving a tenfold cost reduction while maintaining clinical-grade performance. By eliminating extra patient appointments, this workflow shortens the time from diagnosis to treatment from weeks to days, improving patient comfort and substantially enhancing overall clinical efficiency.