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Congress: ECR25
Poster Number: C-16098
Type: Poster: EPOS Radiologist (scientific)
DOI: 10.26044/ecr2025/C-16098
Authorblock: I. Hernandez-Giron1, P. Mchale2, T. Omahony1, R. Byrne1, S. Tracy1; 1Dublin/IE, 2Belfast/UK
Disclosures:
Irene Hernandez-Giron: Nothing to disclose
Peter Mchale: Nothing to disclose
Tristan Omahony: Nothing to disclose
Richard Byrne: Nothing to disclose
Saoirse Tracy: Nothing to disclose
Keywords: Lung, Thorax, CT, CAD, Observer performance, Physics, Cancer, Quality assurance
Purpose To create customized 3D-printed lung nodules (patient and mathematical-based) representative of internationally accepted nodule growth guidelines and variability (shape and composition), from solid to ground glass nodules (GGOs).   To evaluate the X-ray attenuation (with clinical CT systems) and morphometry of the nodules (micro-CT) compared to their design models.  To use such nodules in combination with commercial and 3D-printed lung phantoms for image quality evaluation of CT protocols. 
Read more Methods and materials Background CT technology advances, such as AI-based reconstruction (mostly trained with patient data), present a wide variation of algorithms among manufacturers and little public information about their training datasets and how they operate [1]. To guarantee an optimal use of such technologies with their potential dose reduction for patients, the use of anthropomorphic phantoms should be boosted in CT quality control and image quality evaluation, tracking and optimization [2].  Such phantoms, though some are available in the market, are not widely implemented...
Read more Results 3D printing of lung nodulesSome examples of the 3D printed lung nodules (resin, PA12, TPU), both geoemetric and segmented from patients, are shown in Figure 3 [fig 3] . The printed nodules compared to their original models are shown in Fig 4 [fig 4] . Evaluation of attenuation and morphometry of 3D-printed lung nodules: CT imagingThe CT values (Average±SD) for the selected materials (solid and subsolid nodules) were: [MJF:TPU(60±15HU); PA11(-53±30HU);PA12(-100±45HU);PP(-180±25HU)], [SLS:PA11(-55 ±15HU);PA12(-80 ±20HU)]; [PRUSA:orange-resin(69±20HU);grey-resin(90±32HU)]. For GGOs, the subsolid component was in the range (-630,-550HU). All are in...
Read more Conclusion 3D-printing can be used to create customized lung nodules with different degrees of morphometry and composition complexity (solid, subsolid and ground-glass) compatible with international guidelines. The 3D printed nodules were used in combination with commercial thorax phantoms and 3D printed customized lung vessel phantoms in CT images in a satisfactory way. These nodules could be used to evaluate image quality in CT-thorax imaging and cancer screening programs Such nodules could be used in the future to test the performance of AI-software for lung...
Read more References [1] L.R. Koetzier, D. Mastrodicasa, T.P. Szczykutowicz, N.R. van der Werf, A.S. Wang, V. Sandfort, A.J.vander Molen, D. Fleischmann, and M.J. Willemink, 2023. Deep learning image reconstruction for CT: technicalprinciples and clinical prospects. Radiology, 306(3), p.e221257. https://doi.org/10.1148/radiol.221257[2] ICRP 154: Optimisation of Radiological Protection in Digital Radiology Techniques for Medical Imaging. (2023), Vol.52, nº3. ISBN 9781036206000[3] Siegel RL, et al. Cancer Statistics (CA) , (2025); vol 75(1): 10-45.[4] Harry J. de Koning et al. “Reduced Lung-Cancer Mortality with Volume CTScreening in a Randomized...
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