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PURPOSE:To compare lung densitometric measurements that use a threedimensional (3D) reconstruction of the lungs with those obtained from analysis of two-dimensional (2D) computed tomographic (CT) images, visual emphysema scores, and data from pulmonary function tests. MATERIALS AND METHODS:Thoracic helical CT scans were obtained in 60 adult patients (35 with no visual evidence of emphysema and 25 with emphysema). The lungs were reconstructed as a 3D model on a commercial workstation, with a threshold of Ϫ600 HU. By analysis of histograms, the proportions of lung volumes with attenuation values below Ϫ950, Ϫ910, and Ϫ900 HU were measured, in addition to mean lung attenuation. These values were compared with lung densitometric results obtained from 2D CT images, visual emphysema scores, and data from pulmonary function tests. RESULTS:Quantitation of emphysema with 3D reconstruction was efficient and accurate. Correlation was good among densitometric quantitation with 3D analysis, that obtained with 2D analysis (r ϭ 0.98-0.99), and visual scoring (r ϭ 0.74-0.82). Correlation was reasonable between 3D densitometric quantitation and the diffusing capacity of the lungs for carbon monoxide (DLCO) (r ϭ Ϫ0.57 to Ϫ0.64), total lung capacity (r ϭ 0.62-0.71), forced expiratory volume in 1 second (FEV 1 ) (r ϭ Ϫ0.57 to Ϫ0.60), and the ratio of FEV 1 to forced vital capacity (FVC) (r ϭ Ϫ0.75 to Ϫ0.82). The visual CT quantitation of emphysema correlated best with DLCO (r ϭ Ϫ0.82) and FEV 1 /FVC (r ϭ Ϫ0.89). CONCLUSION:Lung densitometry with 3D reconstruction of helical CT data is a fast and accurate method for quantifying emphysema.Computed tomographic (CT) quantitation of emphysema has been correlated with pulmonary function (1-4) and has been used to predict postoperative function in patients with lung cancer (5); more recently, such quantitation has been used to demonstrate a decrease in emphysema after lung-volume reduction surgery (6-10). The two systems that are used for quantitation of emphysema are visual grading and more objective techniques that use CT software to distinguish pixels with abnormally low attenuation, representing emphysema, from those of normal lung.First applied to two-dimensional (2D) CT sections, the ''density mask'' technique was shown to represent accurately the morphologic extent of emphysema (11) Abbreviations:DLCO ϭ diffusing capacity of the lungs for carbon monoxide FEV 1 ϭ forced expiratory volume in 1 second FVC ϭ forced vital capacity TLC ϭ total lung capacity 2D ϭ two-dimensional 3D ϭ three-dimensional

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Because of unanswered questions about prediction equations for the single-breath carbon monoxide diffusing capacity (DLCO) and as part of a larger collaborative project, standardized DLCO measurements were carried out in a selected sample of 361 healthy nonsmoking volunteers (194 men and 167 women) living in the Barcelona metropolitan area (Spain). Except for the test FIO2 (0.18), the study essentially followed the American Thoracic Society (ATS) and European Community for Coal and Steel (ECCS) recommendations for standardizing the methodology of measuring DLCO. Prediction equations for ages 20 through 70 were calculated separately for both sexes. Simple linear equations using age, height, and body weight as independent variables predicted the DLCO indices (DLCO, VA, and DL/VA) as well as more complex equations. In addition, a complete analysis of the residuals (predicted measured values) showed that the assumptions of the multiple regression analysis (independence, homoscedasticity and Gaussian distribution of residuals) were fulfilled using simple linear equations. Correction for the instrumental and anatomic dead spaces decreased the DLCO an average of 4.7%. The standard error of estimates was lower than those reported from other series in the literature. The predicted values from this study were lower than those reported by some investigators and were in reasonable agreement with other studies. A portion but not all of the differences could be explained on the basis of recognized differences in testing methodology. The results of this study may be of value to clinical laboratories seeking predictive equations for DLCO most appropriate for their testing methodology and patient population, and may assist in the resolution of some controversies regarding differences among predictive equations for DLCO.