Room: Room 207
Purpose: To demonstrate an on-demand and nearly automatic method for fabricating tissue-equivalent physical phantoms using a dual nozzle thermoplastic 3D-printer and two types of plastic.
Methods: Two plastics were investigated: (1) Normal Polylactic acid (PLA) as a soft tissue simulant and (2) Iron PLA, a compound mixture of PLA and an iron powder, as a bone simulant. The plastics and geometry of the torso of an existing 1-year-old computational human phantom were then combined with a dual extrusion 3D-printer to fabricate a customized anthropomorphic imaging phantom. The volumetric fill density of the 3D-printed parts is also varied to approximate tissues of different radiographic density; a calibration curve was generated for each plastic to relate the printer fill density setting to measured CT Hounsfield (HU). A 5 cm section of the torso was split into 5 parts to be printed at full-scale.
Results: The print time for each part was about 12 hours for a total time of 3 days. The model included the lungs, ribs, clavicles, scapulae, sternum, vertebrae, and esophagus. Each tissue was assigned an appropriate plastic and fill density setting to simulate realistic radiographic properties. The soft tissue and lungs were printed using Normal PLA using a fill density of 100% and 35%, respectively. The bones were printed out of Iron PLA with a fill density of 100%. The esophagus was left blank (air). A CT scan of the printed phantom demonstrated excellent similarity to commercially available phantoms. The measured HU of the soft tissue, lung, and bone regions of the phantom was approximately 35, -750, and 2600 HU, respectively.
Conclusion: Patient-specific anthropomorphic phantoms can be 3D-printed and assembled in sections for imaging and dosimetry applications. Such phantoms will be useful for validating computer simulated dosimetry results.
Funding Support, Disclosures, and Conflict of Interest: This work was funded by the intramural program of the National Institutes of Health, National Cancer Institute, Division of Cancer Epidemiology and Genetics.
Not Applicable / None Entered.