TY - JOUR
T1 - Quantifying the extent of emphysema: factors associated with radiologists' estimations and quantitative indices of emphysema severity using the ECLIPSE cohort
AU - Gietema, H.A.
AU - Muller, N.L.
AU - Nasute-Fauerbach, P.V.
AU - Sharma, S.
AU - Edwards, L.D.
AU - Camp, P.G.
AU - ECLIPSE Investigators, (incl. E. Wouters)
AU - Coxson, H.O.
PY - 2011/1/1
Y1 - 2011/1/1
N2 - 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.
AB - 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.
U2 - 10.1016/j.acra.2011.01.011
DO - 10.1016/j.acra.2011.01.011
M3 - Article
C2 - 21393027
SN - 1076-6332
VL - 18
SP - 661
EP - 671
JO - Academic Radiology
JF - Academic Radiology
IS - 6
ER -