PixelPrint: a collection of three-dimensional printed CT phantoms of different respiratory diseases

Kai Mei; Leonid Roshkovan; Pouyan Pasyar; Nadav Shapira; Grace J. Gang; J. Webster Stayman; Michael Geagan; Peter B. Noël

doi:10.1117/12.2654343

7 April 2023 PixelPrint: a collection of three-dimensional printed CT phantoms of different respiratory diseases

Kai Mei, Leonid Roshkovan, Pouyan Pasyar, Nadav Shapira, Grace J. Gang, J. Webster Stayman, Michael Geagan, Peter B. Noël

Author Affiliations +

Proceedings Volume 12463, Medical Imaging 2023: Physics of Medical Imaging; 124633Q (2023) https://doi.org/10.1117/12.2654343
Event: SPIE Medical Imaging, 2023, San Diego, California, United States

Conference Poster

Abstract

Imaging is often a first-line method for diagnostics and treatment. Radiological workflows increasingly mine medical images for quantifiable features. Variability in device/vendor, acquisition protocol, data processing, etc., can dramatically affect quantitative measures, including radiomics. We recently developed a method (PixelPrint) for 3D-printing lifelike computed tomography (CT) lung phantoms, paving the way for future diagnostic imaging standardization. PixelPrint generates phantoms with accurate attenuation profiles and textures by directly translating clinical images into printer instructions that control density on a voxel-by-voxel basis. The present study introduces a library of 3D printed lung phantoms covering a wide range of lung diseases, including usual interstitial pneumonia with advanced fibrosis, chronic hypersensitivity pneumonitis, secondary tuberculosis, cystic fibrosis, Kaposi sarcoma, and pulmonary edema. CT images of the patient-based phantom are qualitatively comparable to original CT images, both in texture, resolution and contrast levels allowing for clear visualization of even subtle imaging abnormalities. The variety of cases chosen for printing include both benign and malignant pathology causing a variety of alveolar and advanced interstitial abnormalities, both clearly visualized on the phantoms. A comparison of regions of interest revealed differences in attenuation below 6 HU. Identical features on the patient and the phantom have a high degree of geometrical correlation, with differences smaller than the intrinsic spatial resolution of the scans. Using PixelPrint, it is possible to generate CT phantoms that accurately represent different pulmonary diseases and their characteristic imaging features.

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Kai Mei, Leonid Roshkovan, Pouyan Pasyar, Nadav Shapira, Grace J. Gang, J. Webster Stayman, Michael Geagan, and Peter B. Noël "PixelPrint: a collection of three-dimensional printed CT phantoms of different respiratory diseases", Proc. SPIE 12463, Medical Imaging 2023: Physics of Medical Imaging, 124633Q (7 April 2023); https://doi.org/10.1117/12.2654343

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