Department of Medical Imaging, The First Affiliated Hospital of Xian Jiaotong University, Xi'an, Shaanxi, China.
Department of Medical Imaging, the Traditional Hospital of Gansu Province, Lanzhou, Gansu, China.
J Xray Sci Technol. 2019;27(4):591-603. doi: 10.3233/XST-180460.
Identification of interstitial lung disease (ILD) may be difficult in certain cases using pulmonary function tests (PFTs) or subjective radiological analysis. We evaluated the efficacy of quantitative computed tomography (CT) with 3-dimensional (3D) reconstruction for distinguishing ILD patients from healthy controls.
We retrospectively collected chest CT images of 102 ILD patients and 102 healthy matched controls, and measured the following parameters: lung parenchymal volume, emphysema indices low attenuation area LAA910 volume, LAA950 volume, LAA910%, and LAA950%, and mean lung density (MLD) for whole lung, left lung, right lung, and each lobe, respectively. The Mann-Whitney U test was used to compare quantitative CT parameters between groups. Receiver operating characteristic (ROC) curves, Bayesian stepwise discriminant analysis, and deep neural network analysis were used to test the discriminative performance of quantitative CT parameters. Binary logistic regression was performed to identify ILD markers.
Total lung volume was lower in ILD patients than controls, while emphysema and MLD values were higher (P < 0.001) except LAA910 volume in right middle lobe. LAA910 volume, LAA950 volume, LAA910%, LAA950%, and MLD accurately distinguished ILD patients from healthy controls (AUC >0.5, P < 0.05), and high MLD was a significant marker for ILD (OR = 1.047, P < 0.05).
This quantitative CT analysis can effectively identify ILD patients, providing an alternative to subjective image analysis and PFTs.
在某些情况下，使用肺功能测试（PFT）或主观放射学分析可能难以识别间质性肺病（ILD）。我们评估了三维（3D）重建定量计算机断层扫描（CT）区分ILD 患者与健康对照的疗效。
我们回顾性收集了 102 例ILD 患者和 102 例健康匹配对照的胸部 CT 图像，并测量了以下参数：肺实质体积、肺气肿指数低衰减区 LAA910 体积、LAA950 体积、LAA910%和 LAA950%，以及全肺、左肺、右肺和每个肺叶的平均肺密度（MLD）。使用 Mann-Whitney U 检验比较组间定量 CT 参数。使用接收者操作特征（ROC）曲线、贝叶斯逐步判别分析和深度神经网络分析测试定量 CT 参数的判别性能。使用二元逻辑回归识别ILD 标志物。
ILD 患者的全肺体积低于对照组，而肺气肿和 MLD 值较高（P<0.001），除右中叶的 LAA910 体积外。LAA910 体积、LAA950 体积、LAA910%、LAA950%和 MLD 准确地区分ILD 患者与健康对照（AUC>0.5，P<0.05），高 MLD 是ILD 的显著标志物（OR=1.047，P<0.05）。
这种定量 CT 分析可以有效地识别ILD 患者，为主观图像分析和 PFT 提供了替代方法。
