Strengths and Limitations of the Study
To the best of our knowledge, our study is the first to use automated CT scan analysis with 3-D filteringA�and voxel density to analyze the association betweenA�radiographic evidence of emphysema and lung cancer.A�This technique has been found to correlate well withA�radiologist assessment of emphysema and physiologicA�data, and to provide reproducible and blinded assessment across CT scan studies. This technique virtually eliminated any subjectivity in the estimation ofA�emphysema, an expressed concern in prior studies; it is interesting to note that the majority of patientsA�with lung cancer and emphysema in the report byA�Wilson et al had either trace or mild emphysema andA�that the association with lung cancer, although statistically significant, did not appear to be linear (no dose-response effect) when all degrees of severity wereA�considered.
The smaller study by de Torres et abA�(23 lung cancers in 1,166 participants) did not analyzeA�severity of emphysema as a predictor of lung cancerA�given that only the presence or absence of emphysema as a dichotomous variable was used. In ourA�study, radiographic evidence of emphysema was analyzed as a continuous variable, thereby theoreticallyA�increasing its power by capturing variability of the dataA�that would be lost with categorical variables hq pharmacy. In addition, we believe that the markedly improved algorithms used in the present study increased theA�sensitivity and specificity of the quantitative analysis ofA�radiographic evidence of emphysema, also leading toA�increased power. Specifically, a dynamic threshold wasA�used to assure accurate extraction of the lungs as wellA�as the iterative tracheal extraction process excludingA�normal structures from the emphysema counts. TheA�differences in emphysema quantification techniqueA�used, in addition to the markedly increased sampleA�size compared with the previous report, are likelyA�responsible for the lower percentage of capturedA�emphysema volume.