SU-G-BRB-01: A Novel 3D Printed Patient-Specific Phantom for Spine SBRT Quality Assurance: Comparison of 3D Printing Techniques

Abstract

Purpose: The novel 3 dimensional (3D)-printed spine quality assurance (QA) phantoms generated by two different 3D-printing technologies, digital light processing (DLP) and Polyjet, were developed and evaluated for spine stereotactic body radiation treatment (SBRT). Methods: The developed 3D-printed spine QA phantom consisted of an acrylic body and a 3D-printed spine phantom. DLP and Polyjet 3D printers using the high-density acrylic polymer were employed to produce spine-shaped phantoms based on CT images. To verify dosimetric effects, the novel phantom was made it enable to insert films between each slabs of acrylic body phantom. Also, for measuring internal dose of spine, 3D-printed spine phantom was designed as divided laterally exactly in half. Image fusion was performed to evaluate the reproducibility of our phantom, and the Hounsfield unit (HU) was measured based on each CT image. Intensity-modulated radiotherapy plans to deliver a fraction of a 16 Gy dose to a planning target volume (PTV) based on the two 3D-printing techniques were compared for target coverage and normal organ-sparing. Results: Image fusion demonstrated good reproducibility of the fabricated spine QA phantom. The HU values of the DLP- and Polyjet-printed spine vertebrae differed by 54.3 on average. The PTV Dmax dose for the DLP-generated phantom was about 1.488 Gy higher than for the Polyjet-generated phantom. The organs at risk received a lower dose when the DLP technique was used than when the Polyjet technique was used. Conclusion: This study confirmed that a novel 3D-printed phantom mimicking a high-density organ can be created based on CT images, and that a developed 3D-printed spine phantom could be utilized in patient-specific QA for SBRT. Despite using the same main material, DLP and Polyjet yielded different HU values. Therefore, the printing technique and materials must be carefully chosen in order to accurately produce a patient-specific QA phantom.