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Evaluating Regional Pulmonary Deposition using Patient-Specific 3D Printed Lung Models
Published on: November 11, 2020
Filament deposition modeling quality assurance testing for the medical physicist
Benjamin T Heggie1, Manuel Arreola1, Stephanie M Leon1
1Department of Radiology, University of Florida, Gainesville, Florida, USA.
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.
