Quantifying the Extent of Emphysema: Factors Associated With Radiologists' Estimations and Quantitative Indices of Emphysema Severity Using the ECLIPSE Cohort

Acad Radiol. 2011 Jun;18(6):661-71. doi: 10.1016/j.acra.2011.01.011. Epub 2011 Mar 9.

Abstract

Rationale and objectives: This study investigated what factors radiologists take into account when estimating emphysema severity and assessed quantitative computed tomography (CT) measurements of low attenuation areas.

Materials and methods: CT scans and spirometry were obtained on 1519 chronic obstructive pulmonary disease (COPD) subjects, 269 smoker controls, and 184 nonsmoker controls from the Evaluation of COPD Longitudinally to Indentify Surrogate Endpoints (ECLIPSE) study. CT scans were analyzed using the threshold technique (%<-950HU) and a low attenuation cluster analysis. Two radiologists scored emphysema severity (0 to 5 scale), described the predominant type and distribution of emphysema, and the presence of suspected small airways disease.

Results: The percent low attenuation area (%LAA) and visual scores of emphysema severity correlated well (r = 0.77, P < .001). %LAA, low attenuation cluster analysis, and absence of radiologist described gas trapping, distribution, and predominant type of emphysema were predictors of visual scores of emphysema severity (all P < .001). CT scans scored as showing regions of gas trapping had smaller lesions for a similar %LAA than those without (P < .001).

Conclusions: Visual estimates of emphysema are not only determined by the extent of LAA, but also by lesion size, predominant type, and distribution of emphysema and presence/absence of areas of small airways disease. A computer analysis of low attenuation cluster size helps quantitative algorithms discriminate low attenuation areas from gas trapping, image noise, and emphysema.

Trial registration: ClinicalTrials.gov NCT00292552.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Aged
  • Algorithms
  • Analysis of Variance
  • Biomarkers
  • Case-Control Studies
  • Cluster Analysis
  • Disease Progression
  • Female
  • Forced Expiratory Volume
  • Humans
  • Longitudinal Studies
  • Male
  • Middle Aged
  • Pulmonary Emphysema / diagnostic imaging*
  • Pulmonary Emphysema / physiopathology
  • Radiographic Image Interpretation, Computer-Assisted
  • Regression Analysis
  • Severity of Illness Index
  • Spirometry
  • Tomography, X-Ray Computed*

Substances

  • Biomarkers

Associated data

  • ClinicalTrials.gov/NCT00292552