Imaging-based clusters in current smokers of the COPD cohort associate with clinical characteristics: the SubPopulations and Intermediate Outcome Measures in COPD Study (SPIROMICS)
Imaging-based clusters in current smokers of the COPD cohort associate with clinical characteristics: the SubPopulations and Intermediate Outcome Measures in COPD Study (SPIROMICS)
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DOI：
10.1186/s12931-018-0888-7
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发表时间：
2018-09-18
影响因子：
5.8
通讯作者：
Lin, Ching-Long
中科院分区：
文献类型：
--
作者：
Haghighi, Babak;Choi, Sanghun;Lin, Ching-Long
背景：COPD的分类通常基于气流的严重程度，这可能无法敏感地区分亚群。使用多尺度成像为基础的聚类分析（云母），我们的目的是确定目前吸烟者与COPD.Methods亚群：在SPIROMICS的主题，我们分析了计算机断层扫描图像在总肺容量（TLC）和剩余容量（RV）的284个目前吸烟者。功能变量来自TLC和RV图像的配准，例如功能性小气道疾病（fSAD%）。在TLC图像上评估结构变量，例如肺气肿和气道壁厚度和直径。我们采用了一种无监督的聚类方法。第1组气道结构相对正常;第2组fSAD%和壁厚增加;第3组fSAD%进一步增加，但壁厚和气道直径减少;第4组fSAD%显著增加，肺气肿。临床上，第1组显示正常FEV 1/FVC和轻度急性加重。第4组显示相对较低的FEV 1/FVC和较高的急性加重。虽然群集2和群集3表现出类似的恶化，群集2有最高的BMI在所有clusters.Conclusions：协会的成像为基础的集群与现有的临床指标表明云母在区分亚群的敏感性。
Background: Classification of COPD is usually based on the severity of airflow, which may not sensitively differentiate subpopulations. Using a multiscale imaging-based cluster analysis (MICA), we aim to identify subpopulations for current smokers with COPD.Methods: Among the SPIROMICS subjects, we analyzed computed tomography images at total lung capacity (TLC) and residual volume (RV) of 284 current smokers. Functional variables were derived from registration of TLC and RV images, e.g. functional small airways disease (fSAD%). Structural variables were assessed at TLC images, e.g. emphysema and airway wall thickness and diameter. We employed an unsupervised method for clustering.Results: Four clusters were identified. Cluster 1 had relatively normal airway structures; Cluster 2 had an increase of fSAD% and wall thickness; Cluster 3 exhibited a further increase of fSAD% but a decrease of wall thickness and airway diameter; Cluster 4 had a significant increase of fSAD% and emphysema. Clinically, Cluster 1 showed normal FEV1/FVC and low exacerbations. Cluster 4 showed relatively low FEV1/FVC and high exacerbations. While Cluster 2 and Cluster 3 showed similar exacerbations, Cluster 2 had the highest BMI among all clusters.Conclusions: Association of imaging-based clusters with existing clinical metrics suggests the sensitivity of MICA in differentiating subpopulations.