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Background Filament deposition modeling (FDM) can be a practical method for producing quality control (QC) imaging resources for the clinic. However, frequent printing may degrade print quality over time. Purpose To develop a process to ensure prints for the diagnostic physicist are accurate and reproducible. Methods Four FDM systems were evaluated by printing a custom, novel QC model on each printer 12 times over a period of 12 months. Several tests were performed, including print resolvability (lp/cm), XYZ dimension accuracy (mm), density (g/cm3), line width (mm), XY position accuracy (mm), clearance fits (mm), and thickness uniformity (mm). Polylactic acid (PLA) samples were printed, measured, and imaged with a dual energy CT scanner. Linear regression models were then created to monitor changes in QC density measurements as a function of x‐ray and material property characteristics (i.e., Hounsfield units and electron density). Between monthly prints, heat uniformity across the build plate was also tested for each printer using a NIST‐certified infrared thermometer and 3D printed grids. All physical measurements were obtained using a calibrated digital caliper and milligram scale. Results Mean percent error (MPE) for all tests was calculated from ground truth (CAD dimensions and filament density) and baseline values (first month of QC measurements). Among printers investigated, MPE was ± 5% of ground truth for all tests except density and thickness uniformity. Baseline MPE was also observed within ± 5% except for resolvability and clearance fit tests among printers. Subtle trend increases were presented for higher density QC prints based on DECT linear regression models. Reduced chi‐squared values indicate uniform and reproducible heat bed temperature measurements. Conclusions This work offers an innovative approach toward evaluating and monitoring FDM system performance. Future work should track performance over a longer time period and across a wider variety of printers.
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Heggie et al. (2026) studied this question.
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