Abstract

PURPOSE: The purpose of this study was to develop a 3-dimensional (3D) printing method to create computed tomography (CT) realistic phantoms of lung cancer nodules and lung parenchymal disease from clinical CT images.MATERIALS AND METHODS: Low-density paper was used as substrate material for inkjet printing with potassium iodide solution to reproduce phantoms that mimic the CT attenuation of lung parenchyma. The relationship between grayscale values and the corresponding CT numbers of prints was first established through the derivation of exponential fitted equation from scanning data. Next, chest CTs from patients with early-stage lung cancer and coronavirus disease 2019 (COVID-19) pneumonia were chosen for 3D printing. CT images of original lung nodule and the 3D-printed nodule phantom were compared based on pixel-to-pixel correlation and radiomic features.RESULTS: CT images of part-solid lung cancer and 3D-printed nodule phantom showed both high visual similarity and quantitative correlation. R2 values from linear regressions of pixel-to-pixel correlations between 5 sets of patient and 3D-printed image pairs were 0.92, 0.94, 0.86, 0.85, and 0.83, respectively. Comparison of radiomic measures between clinical CT and printed models demonstrated 6.1% median difference, with 25th and 75th percentile range at 2.4% and 15.2% absolute difference, respectively. The densities and parenchymal morphologies from COVID-19 pneumonia CT images were well reproduced in the 3D-printed phantom scans.CONCLUSION: The 3D printing method presented in this work facilitates creation of CT-realistic reproductions of lung cancer and parenchymal disease from individual patient scans with microbiological and pathology confirmation.

View details for DOI 10.1097/RTI.0000000000000607

View details for PubMedID 34334783