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Fig. 2 | Respiratory Research

Fig. 2

From: A fully automated micro‑CT deep learning approach for precision preclinical investigation of lung fibrosis progression and response to therapy

Fig. 2

Qualitative longitudinal monitoring of lung fibrosis progression in BLM- and BLM + NINT-treated mice. A Representative 3D renderings of the lungs at the end of the end-expiratory phase (P02) derived from a randomly chosen animal per group (SAL, BLM, and BLM + NINT). Different degrees of lung aeration are shown as false colors (blue: normo-aerated; pink: hypo-aerated; grey: non-aerated). 3D renderings of the lungs from BLM- and BLM + NINT-treated mice were generated for each time-point (7, 14, 21 days) in order to longitudinally monitor changes in shape and aeration compartments. The representative SAL lung has 81.4% normo-aerated tissue and 18.6% hypo-aerated tissue. In the BLM and BLM + NINT representative cases the %non-aerated tissue increased from day 7 to 21, respectively from 1.5% to 38.9%, and from 6.2% to 12.2%; the %hypo-aerated compartment increased from day 7 to 21, respectively from 24.7% to 38,4%, and from 36.1% to 39.1%. On the contrary, the %normo-aerated tissue decreased in both groups from day 7 to 21, respectively from 73.8% to 22.7%, and from 57.7% to 48.7%. B Representative µCT 2D coronal slices of the same lung images shown in A acquired at the end-expiratory phase (P02); cyan-colored, low-intensity pixels represent the air content of the lungs

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