Applied Chest Imaging Laboratory, Brigham and Women's Hospital; Boston, MA.
Applied Chest Imaging Laboratory, Brigham and Women's Hospital; Boston, MA; Division of Pulmonary and Critical Care Medicine, Department of Medicine, Brigham and Women's Hospital, Boston, MA.
Chest. 2019 Dec;156(6):1149-1159. doi: 10.1016/j.chest.2019.05.020. Epub 2019 Jun 22.
Tobacco smoke exposure is associated with emphysema and pulmonary fibrosis, both of which are irreversible. We have developed a new objective CT analysis tool that combines densitometry with machine learning to detect high attenuation changes in visually normal appearing lung (Norm) that may precede these diseases.
We trained the classification tool by placing 34,528 training points in chest CT scans from 297 COPDGene participants. The tool was then used to classify lung tissue in 9,038 participants as normal, emphysema, fibrotic/interstitial, or Norm. Associations between the quartile of Norm and plasma-based biomarkers, clinical severity, and mortality were evaluated using Jonckheere-Terpstra, pairwise Wilcoxon rank-sum tests, and multivariable linear and Cox regression.
A higher percentage of lung occupied by Norm was associated with higher C-reactive protein and intercellular adhesion molecule 1 (P for trend for both < .001). In analyses adjusted for multiple covariates, including high and low attenuation area, compared with those in the lowest quartile of Norm, those in the highest quartile had a 6.50 absolute percent lower percent predicted lower FEV (P < .001), an 8.48 absolute percent lower percent predicted forced expiratory volume, a 10.78-meter shorter 6-min walk distance (P = .011), and a 56% higher risk of death (P = .003). These findings were present even in those individuals without visually defined interstitial lung abnormalities.
A new class of Norm on CT may represent a unique tissue class associated with adverse outcomes, independent of emphysema and fibrosis.
吸烟暴露与肺气肿和肺纤维化有关，这两种疾病都是不可逆转的。我们开发了一种新的 CT 分析工具，该工具结合了密度测定和机器学习，以检测在外观正常的肺部（Norm）中可能先于这些疾病出现的高衰减变化。
我们通过在 297 名 COPDGene 参与者的胸部 CT 扫描中放置 34528 个训练点来训练分类工具。然后，该工具用于将 9038 名参与者的肺部组织分为正常、肺气肿、纤维化/间质或 Norm。使用 Jonckheere-Terpstra、两两 Wilcoxon 秩和检验以及多变量线性和 Cox 回归评估 Norm 四分位数与基于血浆的生物标志物、临床严重程度和死亡率之间的关联。
Norm 所占肺部百分比越高，C 反应蛋白和细胞间黏附分子 1 越高（两者的趋势 P <.001）。在调整了多个协变量（包括高低衰减区）的分析中，与 Norm 最低四分位数的参与者相比，最高四分位数的参与者的预测 FEV 绝对百分比低 6.50%（P <.001），预测用力呼气量绝对百分比低 8.48%，6 分钟步行距离短 10.78 米（P =.011），死亡风险高 56%（P =.003）。即使在没有视觉定义的间质性肺异常的个体中，也存在这些发现。
CT 上的新一类 Norm 可能代表一种与不良结局相关的独特组织类型，与肺气肿和纤维化无关。
