Multi-scale analysis of imaging features to study exacerbation susceptible COPD
Multi-scale analysis of imaging features to study exacerbation susceptible COPD
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影像学特征的多尺度分析研究慢性阻塞性肺病易恶化的情况
DOI：
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发表时间：
2014
期刊：
影响因子：
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通讯作者：
J. Hurst
中科院分区：
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作者：
Felix J. S. Bragman;J. McClelland;D. Hawkes;J. Hurst
尽管影像学方面取得了进展，但疾病分布与COPD急性加重的病理生理学之间的联系尚不清楚。我们假设，一种新的方法，使用区域分析的CT衍生的影像学特征，代表肺结构和生理，可以跟踪加重易感表型。该研究是在来自COPD基因研究的GOLD 3患者的CT图像上进行的，其恶化频率为每年0和>6（均n=8）。两组的平均年龄分别为67.5岁和60.2岁，FEV1%预测值分别为40.5岁和42.1岁，FEV 1 /FVC分别为42.4岁和47.2岁。配对屏气图像的配准用于获得27个特征，代表整个肺和单个肺叶的组织结构和功能。这些包括平均体积变化（行列式雅可比矩阵）、应变各向异性（Var（e））、应变幅度的总体测量（∑（e））和组织密度（体素强度）。我们观察到在肺叶水平上的特征之间存在显著差异，主要是在下肺叶内，但在整个肺尺度上没有显著性。这些初步数据表明，可以检测到肺结构和功能的区域性改变，这可能有助于COPD急性加重的易感性。
Despite advances in imaging, the link between the distribution of disease and pathophysiology of exacerbations in COPD is unknown. We hypothesised that a new method, using regional analysis of CT-derived imaging features representing lung structure and physiology, can track exacerbation susceptible phenotypes. The study was performed on CT images of GOLD 3 patients from the COPDGene study with exacerbation frequencies of 0 and >6 per year (both n=8). The groups had mean age 67.5 and 60.2 years, FEV 1 %predicted 40.5 and 42.1 and FEV 1 /FVC 42.4 and 47.2 respectively. Registration of paired breath-hold images was used to derive 27 features, representing tissue structure and function over the full lung and individual lobes. These included the mean volume change (determinant Jacobian), anisotropy in strain (Var(e)), an overall measure of strain magnitude (∑(e)) and tissue density (voxel intensity). We observed marked differences between features at the lobar level, principally within lower lobes yet no significance at the whole lung scale. These pilot data suggest that regional alterations in lung structure and function can be detected, which may inform on COPD exacerbation susceptibility.