Fig. 3From: A fully automated micro‑CT deep learning approach for precision preclinical investigation of lung fibrosis progression and response to therapyLongitudinal assessment of morphological µCT biomarkers in the P02 phase for the whole, left, and right lungs. A Quantification of the Normo-aerated compartment expressed as percentage (%Normo). B Quantification of the Hypo-aerated compartment expressed as percentage (%Hypo). C Quantification of the Non-aerated compartment expressed as a percentage (%Non). D Lung volume without gas (Tissue) quantification. All values reported for the BLM and BLM + NINT groups were normalized with respect to the mean values of the SAL group averaged on days 7, 14, and 21, except for %Non which is expressed as absolute percentage value. The black lines set at 1.0 represent the “untreated” condition obtained by dividing the SAL mean value by itself, while in C the black line is set at 0. BLM (red) and BLM + NINT (green) data are given as mean ± SEM. Statistical significance of longitudinal changes of CT parameters in the BLM and BLM + NINT groups was assessed by Two-way ANOVA followed by Šidák post-hoc test (#p < 0.05; ##p < 0.01; ### p < 0.001). Statistical significance of differences between groups was calculated by Two-way ANOVA followed by Dunnett’s t post-hoc test (*p < 0.05; **p < 0.01; ***p < 0.001 vs. BLM group) and the relative percentage of inhibition (−) or recovery (+) at 21 days was reported at the top right-side of each plotBack to article page