In this work, we compare two methods for evaluating and quantifying pulmonary airspace enlargement in a mouse model of chronic cigarette smoke exposure. Standard stereological sample preparation, sectioning, and imaging of mouse lung tissues were performed for semi-automated acquisition of mean linear intercept (L_m) data. After completion of the L_m measurements, D₂, a metric of airspace enlargement, was measured in a blinded manner on the same lung images using a fully automated technique developed in-house. An analysis of variance (ANOVA) shows that although L_m was able to separate the smoke-exposed and control groups with statistical significance (p = 0.034), D₂ was better able to differentiate the groups (p<0.001) and did so without any overlap between the control and smoke-exposed individual animal data. In addition, the fully automated implementation of D₂ represented a time savings of at least 24x over semi-automated L_m measurements. Although D₂ does not provide 3D stereological metrics of airspace dimensions as L_m does, results show that it has higher sensitivity and specificity for detecting the subtle airspace enlargement one would expect to find in mild or early stage emphysema. Therefore, D₂ may serve as a more accurate screening measure for detecting early lung disease than L_m.