Environmental Health and Safety, Stanford University.
Stanford University School of Medicine, Stanford.
J Thorac Imaging. 2022 May 1;37(3):146-153. doi: 10.1097/RTI.0000000000000607. Epub 2021 Aug 2.
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.
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.
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.
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.
本研究旨在开发一种 3 维(3D)打印方法,从临床 CT 图像创建肺癌结节和肺实质疾病的 CT 逼真体模。
低密度纸用作喷墨打印的基底材料,用碘化钾溶液复制模拟肺实质 CT 衰减的体模。首先通过从扫描数据推导出指数拟合方程,建立灰度值与打印品相应 CT 数之间的关系。然后,选择来自早期肺癌患者和 2019 冠状病毒病(COVID-19)肺炎患者的胸部 CT 进行 3D 打印。基于像素对像素相关性和放射组学特征,对原始肺结节的 CT 图像和 3D 打印结节体模进行比较。
部分实性肺癌 CT 图像和 3D 打印结节体模均具有较高的视觉相似性和定量相关性。5 组患者与 3D 打印图像对之间像素对像素相关性的线性回归 R2 值分别为 0.92、0.94、0.86、0.85 和 0.83。对临床 CT 和打印模型的放射组学测量值进行比较,中位数差异为 6.1%,绝对差异的 25%和 75%分位范围分别为 2.4%和 15.2%。COVID-19 肺炎 CT 图像的密度和实质形态在 3D 打印体模扫描中得到很好的复制。
本研究提出的 3D 打印方法有助于从具有微生物学和病理学确认的个体患者扫描中创建 CT 逼真的肺癌和实质疾病复制体。