Clinical relevance of accuracy in in-house 3D printing in craniomaxillofacial surgery: A comparative study of FFF, SLA, and MJ Technologies

Background Considering the Medical Device Regulation (MDR 2017/745), this study aims to evaluate the accuracy of three commonly used 3D printing technologies—Fused Filament Fabrication (FFF), Stereolithography (SLA), and Material Jetting (MJ)—within a clinically realistic in-house 3D printing workflow. Methods In this study, the accuracy of 3D printers was assessed using highly accurate anatomical models to mimic an in vitro clinical workflow, unlike previous validation studies that relied on geometric calibration models or simplified shapes.Accuracy was defined through precision (intra- and inter-build variability) and trueness (deviation from the digital reference model), quantified using root mean square (RMS) error.To analyse the data structure—comprising repeated prints, multiple models, and timepoints—we used a Linear Mixed Model (LMM), which enabled evaluation of fixed effects (printer type, anatomical model, and comparison type) while correcting for internal clustering of data. Results All printers achieved clinically acceptable accuracy. MJ was significantly more accurate (RMS 67 µm) compared to SLA (109 µm) and FFF (130 µm). The Linear Mixed Model showed that accuracy was influenced by printer type and anatomical complexity. Conclusion This is the first study in 3D printing accuracy research to apply a Linear Mixed Model, providing a statistically robust analysis framework. Among the evaluated technologies, MJ achieved the highest accuracy in clinically realistic conditions, supporting its use in applications that require high anatomical fidelity within the MDR framework.