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

Amir M. Owrangi, Roya Etemad-Rezai, David G. McCormack, Ian A. Cunningham, Grace Parraga

Research output: Contribution to journalArticle

9 Citations (Scopus)

Abstract

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 3He 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 3He 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 3He 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 3He magnetic resonance imaging ADCs.

Original languageEnglish (US)
Pages (from-to)537-545
Number of pages9
JournalAcademic Radiology
Volume20
Issue number5
DOIs
StatePublished - May 1 2013

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Pulmonary Emphysema
Emphysema
Vital Capacity
Forced Expiratory Volume
Principal Component Analysis
Tomography
Chronic Obstructive Pulmonary Disease
Lung Volume Measurements
Diffusion Magnetic Resonance Imaging
Carbon Monoxide
Lung
Plethysmography
Spirometry
Respiratory Function Tests
Informed Consent
Linear Models
X-Rays

Keywords

  • Computed tomography
  • COPD
  • Emphysema
  • Principal component analysis

ASJC Scopus subject areas

  • Radiology Nuclear Medicine and imaging

Cite this

Computed tomography density histogram analysis to evaluate pulmonary emphysema in ex-smokers. / Owrangi, Amir M.; Etemad-Rezai, Roya; McCormack, David G.; Cunningham, Ian A.; Parraga, Grace.

In: Academic Radiology, Vol. 20, No. 5, 01.05.2013, p. 537-545.

Research output: Contribution to journalArticle

Owrangi, Amir M. ; Etemad-Rezai, Roya ; McCormack, David G. ; Cunningham, Ian A. ; Parraga, Grace. / Computed tomography density histogram analysis to evaluate pulmonary emphysema in ex-smokers. In: Academic Radiology. 2013 ; Vol. 20, No. 5. pp. 537-545.
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AU - Cunningham, Ian A.

AU - Parraga, Grace

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N2 - 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 3He 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 3He 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 3He 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 3He magnetic resonance imaging ADCs.

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