A statistical comparison was made between manual and automatic measurements of D0, D1, and D2 to determine how well the individual measurements for the two methods correlated and whether or not there was an overall difference in mean values for each variable. Pearson correlation coefficients were calculated, and analysis of variance along with two sample t-tests were used to establish if differences existed between the measurement methods. ANOVA procedures were also performed to determine if D2 and Lm were equally effective in detecting significant differences between smoke-exposed mice and those in the control group. In these statistical analyses, a significance level of 0.05 was used. Additionally, linear discriminate analysis was used to create classification rules to predict the specificity and the sensitivity for D2 and Lm. In this study we compared two methods for quantifying airspace enlargement in smoke-exposed mice. We followed standard procedures for lung tissue sample preparation, image acquisition, and Lm analysis. Following this, we calculated the new index, D2, on the same images to compare how well the two methods separate the smoke-exposed and control groups. Our results show that D2 was better able to distinguish between the groups, and this is attributed to the fact that D2 is weighted by enlarged airspaces and is therefore a reflection of the airspace size distribution. Lm, on the other hand, is a measure of the intraalveolar septal wall mean free path and tends to mask the presence of sparse, enlarged airspaces. We emphasize that D2 does not provide information about the actual airspace geometries; rather, it simply offers a more sensitive metric of airspace enlargement. A manual Danshensu (sodium salt) biological activity validation of the automated D2 measurements was performed to assure that the Ametycine automation did not misinterpret features and would not adversely affect the results. Figures 4 and 5, with accompanying statistical analysis, confirm that full automation did not introduce appreciable errors. We note that the difference in scatter in the top panel of Figure 5 versus that of the bottom panel illustrates that small discrepancies in thresholding, particularly of the smallest airspaces, are outweighed by the effects of the largest airspaces and are, therefore, generally not significant. This point underscores the robustness of the automated method. Still, there may be cases when a semi-automated implementation may be necessary,
