Computed tomography density histogram analysis to evaluate pulmonary emphysema in ex-smokers.

RATIONALE AND OBJECTIVES

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.

MATERIALS AND METHODS

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.

RESULTS

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.

CONCLUSIONS

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.