Abstract Accurate lung function assessment is essential in preclinical idiopathic pulmonary fibrosis (IPF) research, yet conventional whole-lung endpoints overlook spatial heterogeneity and compensatory mechanisms. We present a µCT-based pipeline for longitudinal, regional quantification of structural and functional changes in a murine bleomycin (BLM)-induced fibrosis model to improve evaluation of disease progression and therapeutic effects. C57BL/6 mice received triple oropharyngeal administrations of saline or BLM. Respiratory-gated µCT scans were acquired in free-breathing at baseline and days 7, 14, and 21. A deep-learning algorithm segmented the lungs into left and right lobes, further subdivided into apical and caudal regions using airway landmarks. Regional volumes, aeration compartments, and ventilation maps were extracted to assess structural and functional alterations. Saline-treated mice showed stable metrics over time, with minimal inter-animal variability, demonstrating the robustness and physiological consistency of our segmentation procedure. BLM-treated animals exhibited early and heterogeneous fibrotic changes, with the apical regions appearing as most affected. The caudal-right region displayed a compensatory functional increase of respiratory parameters derived from multivolume µCT. µCT-based regional analysis can detect localized dysfunction and compensatory effects not captured by whole-lung measurements. This strategy is applicable to different models of heterogeneous lung disease and may contribute to reduce the translational gap in IPF research.
Buccardi et al. (Sat,) studied this question.