@inproceedings{8d5c95ae82fd40a78f6707664df324a5,
title = "PixelPrint: Three-dimensional printing of patient-specific soft tissue and bone phantoms for CT",
abstract = "Patient-based CT phantoms, with realistic image texture and densities, are essential tools for assessing and verifying CT performance in clinical practice. This study extends our previously presented 3D printing solution (PixelPrint) to patient-based phantoms with soft tissue and bone structures. To expand the Hounsfield Unit (HUs) range, we utilize a stone-based filament. Applying PixelPrint, we converted patient DICOM images directly into FDM printer instructions (G-code). Density was modeled as the ratio of filament to voxel volume to emulate attenuation profiles for each voxel, with the filament ratio controlled through continuous modification of the printing speed. Two different phantoms were designed to demonstrate the high reproducibility of our approach with micro-CT acquisitions, and to determine the mapping between filament line widths and HU values on a clinical CT system. Moreover, a third phantom based on a clinical cervical spine scan was manufactured and scanned with a clinical spectral CT scanner. CT image of the patient-based phantom closely resembles the original CT image both in texture and contrast levels. Measured differences between patient and phantom are around 10 HU for bone marrow voxels and around 150 HU for cortical bone. In addition, stone-based filament can accurately represent boney tissue structures across the different x-ray energies, as measured by spectral CT. This study demonstrates the feasibility of our 3D-printed patient-based phantoms to be extended to soft-tissue and bone structure while maintaining accurate organ geometry, image texture, and attenuation profiles for spectral CT.",
keywords = "3D printing, Computed Tomography, Image Quality Phantoms, Quality Assurance",
author = "Kai Mei and Michael Geagan and Nadav Shapira and Liu, {Leening P.} and Pouyan Pasyar and Jianan Gang and Stayman, {J. Webster} and No{\"e}l, {Peter B.}",
note = "Funding Information: The authors acknowledge support through the National Institutes of Health (R01EB030494). Publisher Copyright: {\textcopyright} 2022 SPIE.; 7th International Conference on Image Formation in X-Ray Computed Tomography ; Conference date: 12-06-2022 Through 16-06-2022",
year = "2022",
doi = "10.1117/12.2647008",
language = "English (US)",
series = "Proceedings of SPIE - The International Society for Optical Engineering",
publisher = "SPIE",
editor = "Stayman, {Joseph Webster}",
booktitle = "7th International Conference on Image Formation in X-Ray Computed Tomography",
}