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

Area of Science:

• Medical imaging
• Additive manufacturing
• Bioprinting

Background:

• Additive manufacturing (AM) and bioprinting enable patient-specific anatomical models from medical scans.
• The geometric accuracy of 3D printed constructs depends on multiple steps in model derivation.
• Accurate 3D printed models are vital for surgical planning, medical education, and tissue engineering.

Purpose of the Study:

• To compare the dimensional accuracy of 3D printed L1 vertebra models with the original ex vivo vertebra.
• To evaluate the impact of segmentation, filtering, and surface extraction on model dimensions.
• To investigate the influence of CT reconstruction kernels on derived model dimensions.

Main Methods:

• 3D printing of an L1 vertebra from CT data using a MakerBot Replicator 2 printer and polylactic acid (PLA) filament.
• Evaluation of binary median filters and surface extraction algorithms for their effect on model dimensions.
• Scanning simple geometric objects to assess the impact of CT reconstruction kernels on derived dimensions.

Main Results:

• Changes in scan reconstruction, segmentation, filtering, and surface extraction parameters affect the final 3D model dimensions.
• Significant differences can exist between physical and virtual model measurements.
• The study identified key processing steps that influence the dimensional accuracy of 3D printed anatomical models.

Conclusions:

• The accuracy of 3D printed anatomical models is sensitive to variations in the data processing pipeline.
• Quantification of these dimensional effects is essential for applications in medicine and tissue engineering.
• Further research is needed to establish standardized protocols for accurate 3D model generation.