Abstract: Objective. To define the sensitivity of microcomputed tomography- (micro-CT-) derived descriptors for the quantification of lung damage caused by elastase instillation. Materials and Methods. The lungs of 30 elastase treated and 30 control A/J mice were analyzed 1, 6, 12, and 24 hours and 7 and 17 days after elastase instillation using (i) breath-hold-gated micro-CT, (ii) pulmonary function tests (PFTs), (iii) RT-PCR for RNA cytokine expression, and (iv) histomorphometry. For the latter, an automatic, parallel software toolset was implemented that computes the airspace enlargement descriptors: mean linear intercept (Lm) and weighted means of airspace diameters (D0, D1, and D2). A Support Vector Classifier was trained and tested based on three nonhistological descriptors using as ground truth. Results. D2 detected statistically significant differences (P < 0.01) between the groups at all time points. Furthermore, D2 at 1 hour (24 hours) was significantly lower (P < 0.01) than D2 at 24 hours (7 days). The classifier trained on the micro-CT-derived descriptors achieves an area under the curve (AUC) of 0.95 well above the others (PFTS AUC = 0.71; cytokine AUC = 0.88). Conclusion. Micro-CT-derived descriptors are more sensitive than the other methods compared, to detect in vivo early signs of the disease.
area under the curves; cytokine expression; cytokines; descriptors; elastase; ground truth; histomorphometry; in-vivo; micro ct; microcomputed tomography; mouse models; parallel software; pulmonary function test; statistically significant difference; support vector classifiers; time points; weighted mean; biological organs; mammals; polymerase chain reaction; rna; computerized tomography