Pulmonary Fibrosis (PF) is a severe interstitial lung disease characterized by a poor prognosis and limited response to current therapies. As the disease progresses, the continuous build-up of fibrotic tissue causes the lung architecture to become increasingly rigid, leading to a gradual and devastating decline in respiratory function.
Despite a wealth of experimental data identifying pathogenic mechanisms and promising therapeutic targets, only a few drugs are currently available for PF. Worse, these treatments can only slow disease progression, they cannot halt or reverse it. Bridging this “bench-to-bedside” translational gap has been a major challenge, largely because current pre-clinical animal models often fail to perfectly mimic human PF disease progression and screening techniques.
A study published by Dekoster, K., et al, (2020) in Nature Scientific Reports highlights a powerful approach to overcoming these limitations: using longitudinal biomarkers in pre-clinical models to identify early, critical windows for therapeutic intervention.
Instead of the classic Bleomycin model, the researchers chose a silica-induced model of PF. Why? Because silica exposure creates a persistent, non-resolving fibrosis that more closely resembles human PF. It provides a longer disease window, making it far more effective for testing long-term disease progression and the efficacy of new therapeutics.
To monitor the progression of experimental silica-induced PF, the research team utilized longitudinal micro-computed tomography (micro-CT). This non-invasive imaging technique allowed them to extract two primary biomarkers:
Non-Aerated Lung Volume: Serves as a biomarker for the degree of fibrotic pathology.
Aerated Lung Volume: Serves as a biomarker for remaining lung function.
Overall, the scans revealed that both aerated and non-aerated lung volumes increased significantly in the silica-induced model compared to the saline-treated control group.
To ensure the micro-CT findings accurately reflected true physiological changes, the researchers cross-validated the imaging data with end-point lung mechanics, inflammatory evaluations, and histopathological analysis.
They utilized the flexiVent system to deeply characterize complete lung function at every target endpoint. The results demonstrated strong correlations between the non-invasive micro-CT biomarkers and both clinical lung mechanics and biological readouts:
| Micro-CT Biomarker | Correlated Lung Mechanics (flexiVent) | Correlated Biological Readouts |
| Total Lung Volume | Tissue hysteresivity | N/A |
| Non-Aerated Lung Volume | Clinically translatable flow limitation | BAL protein, Serum protein, Hydroxyproline |
| Aerated Lung Volume | Inspiratory capacity | N/A |
This study proves that in vivo longitudinal micro-CT-derived biomarkers allow for the validated identification and quantification of disease progression. By combining advanced imaging with precise lung mechanics testing (like the flexiVent), researchers can successfully track silica-induced PF over time. Ultimately, utilizing these highly translatable methodologies helps bridge the gap between pre-clinical fibrosis models and human clinical trials, paving the way for more effective PF treatments.
Dekoster, K., et al. (2020). Scientific Reports, 10: 16181. Longitudinal micro-computed tomography-derived biomarkers quantify non-resolving lung fibrosis in a silicosis mouse model.
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