Factors Affecting Dimensional Accuracy of 3-D Printed Anatomical Structures Derived from CT Data

Abstract

Additive manufacturing and bio-printing, with the potential for direct fabrication of complex patient-specific anatomies derived from medical scan data, are having an ever-increasing impact on the practice of medicine. Anatomic structures are typically derived from CT or MRI scans, and there are multiple steps in the model derivation process that influence the geometric accuracy of the printed constructs. In this work, we compare the dimensional accuracy of 3-D printed constructs of an L1 vertebra derived from CT data for an ex vivo cadaver T-L spine with the original vertebra. Processing of segmented structures using binary median filters and various surface extraction algorithms is evaluated for the effect on model dimensions. We investigate the effects of changing CT reconstruction kernels by scanning simple geometric objects and measuring the impact on the derived model dimensions. We also investigate if there are significant differences between physical and virtual model measurements. The 3-D models were printed using a commercial 3-D printer, the Replicator 2 (MakerBot, Brooklyn, NY) using polylactic acid (PLA) filament. We found that changing parameters during the scan reconstruction, segmentation, filtering, and surface extraction steps will have an effect on the dimensions of the final model. These effects need to be quantified for specific situations that rely on the accuracy of 3-D printed models used in medicine or tissue engineering applications.