Imaging Research Laboratories, Robarts Research Institute, 100 Perth Drive, London, Canada N6A 5K8.
Acad Radiol. 2013 May;20(5):537-45. doi: 10.1016/j.acra.2012.11.010.
High-resolution computed tomography (CT) measurements of emphysema typically use Hounsfield unit (HU) density histogram thresholds or observer scores based on regions of low x-ray attenuation. Our objective was to develop an automated measurement of emphysema using principal component analysis (PCA) of the CT density histogram.
Ninety-seven ex-smokers, including 53 subjects with chronic obstructive pulmonary disease (COPD) and 44 asymptomatic subjects (AEs), provided written informed consent to imaging as well as plethysmography and spirometry. We applied PCA to the CT density histogram to generate whole lung and regional density histogram principal components including the first and second components and the sum of both principal components (density histogram principal component score [DHPCS]). Significant relationships for DHPCS with single HU thresholds, pulmonary function measurements, an expert's emphysema score, and hyperpolarized (3)He magnetic resonance imaging apparent diffusion coefficients (ADCs) were determined using linear regression and Pearson coefficients. Receiver operator characteristics analysis was performed using forced expiratory volume in 1 second (FEV1)/forced vital capacity (FVC) as the independent diagnostic.
There was a significant difference (P < .0001) between AE and COPD subjects for DHPCS; FEV1/FVC; diffusing capacity of lung for carbon monoxide%predicted; attenuation values below -950, -910, and -856 HU; and (3)He ADCs. There were significant correlations for DHPCS with FEV1/FVC (r = -0.85, P < .0001); diffusing capacity of lung for carbon monoxide%predicted (r = -0.67, P < .0001); attenuation values below -950/-910/-856 HU (r = 0.93/0.96/0.76, P < .0001); and (3)He ADCs (r = 0.85, P < .0001). Receiver operator characteristics analysis showed a 91% classification rate for DHPCS.
We generated an automated emphysema score using PCA of the CT density histogram with a 91% COPD classification rate that showed strong and significant correlations with pulmonary function tests, single HU thresholds, and (3)He magnetic resonance imaging ADCs.
高分辨率计算机断层扫描（CT）对肺气肿的测量通常使用亨氏单位（HU）密度直方图阈值或基于低 X 射线衰减区域的观察者评分。我们的目标是使用 CT 密度直方图的主成分分析（PCA）来开发一种自动测量肺气肿的方法。
97 名戒烟者，包括 53 名慢性阻塞性肺疾病（COPD）患者和 44 名无症状受试者（AEs），对成像以及体积描记法和肺活量测定法均提供了书面知情同意。我们将 PCA 应用于 CT 密度直方图，生成包括第一和第二分量以及两个主分量之和的全肺和区域密度直方图主分量（密度直方图主分量得分[DHPCS]）。使用线性回归和 Pearson 系数确定 DHPCS 与单个 HU 阈值、肺功能测量、专家肺气肿评分和超极化（3）氦磁共振成像表观扩散系数（ADC）之间的显著关系。使用 1 秒用力呼气量（FEV1）/用力肺活量（FVC）作为独立诊断进行接收器工作特性分析。
AE 和 COPD 患者的 DHPCS 之间存在显著差异（P<0.0001）；FEV1/FVC；一氧化碳弥散量%预计值；衰减值低于-950、-910 和-856 HU；和（3）氦 ADCs。DHPCS 与 FEV1/FVC（r=-0.85，P<0.0001）；一氧化碳弥散量%预计值（r=-0.67，P<0.0001）；衰减值低于-950/-910/-856 HU（r=0.93/0.96/0.76，P<0.0001）；和（3）氦 ADCs（r=-0.85，P<0.0001）。接收器工作特性分析显示 DHPCS 的分类率为 91%。
我们使用 CT 密度直方图的 PCA 生成了一种自动肺气肿评分，COPD 的分类率为 91%，与肺功能测试、单个 HU 阈值和（3）氦磁共振成像 ADC 具有很强的显著相关性。
