qPulmoFib Imaging: A novel quantitative evaluation method based on optical imaging technology for precise staging and early diagnosis of idiopathic pulmonary fibrosis in animal models

Background: Idiopathic pulmonary fibrosis (IPF) is a highly malignant and irreversible interstitial lung disease. Accurate assessment is crucial for understanding its pathological mechanisms and formulating treatment strategies. Although the Ashcroft scoring system is widely used clinically, it relies primarily on qualitative visual judgment and cannot quantify key features of collagen fibers, thus significantly limiting the precise differentiation of fibrosis stages. Objective: This study established a mouse IPF model using bleomycin (BLM) to develop a new quantitative evaluation method to enhance the precise differentiation of lung fibrosis stages. Method: Lung tissues of mice were observed at 0, 3, 5, 7, 11, and 14 days. Initially, traditional Masson staining and the Ashcroft scoring system were used for preliminary evaluation of lung fibrosis, which lacks quantitative assessment of collagen fibers. To overcome this limitation, this study combined advanced optical imaging technology and image analysis software. Second harmonic generation (SHG) and liquid Crystal polarized light microscopy (LCPLM) were used for detailed observation and quantitative analysis of collagen fibers in unstained lung tissue sections. Additionally, FITC-labeled pulmonary vessels, combined with two-photon excited fluorescence (TPEF) + SHG imaging, provided three-dimensional imaging of collagen fibers and blood vessels in lung tissue, enhancing understanding of their spatial distribution. Detailed quantitative analysis from single fibers to the entire fiber network was achieved using the CurveAlign tool in MATLAB. Results: Compared to the traditional Ashcroft scoring system, this study established a new evaluation method- Quantitative pulmonary fibrosis imaging (qPulmoFib Imaging). By quantifying specific characteristics of collagen fibers, it not only faithfully replicated the results of traditional scoring but also refined the features of various stages of lung fibrosis and showed significant advantages in detecting early morphological changes in fibrosis (P < 0.01). SHG observations showed that the coefficients of variation in width and length (Width. CV and Length. CV) of collagen fibers in unstained sections significantly distinguished samples from 0-3 days and 11-14 days (P < 0.01). Furthermore, collagen fiber characteristic parameters obtained through TPEF+SHG technology also showed high differentiation between 0-5 days and 11-14 days (P < 0.01). Pulmonary function parameters (breathing rate and inspiratory flow) correlated well with fibrosis parameters in qPulmoFib Imaging (R-2>0.60), confirming the pathological relevance of the new method. Conclusion: This study developed qPulmoFib Imaging, which quantifies core characteristics of collagen fibers, enabling precise staging of lung fibrosis in early diagnosis and late stages. It provides a more accurate and objective quantitative analysis tool than traditional scoring systems. The successful application of this method not only advances the understanding of IPF pathological processes but also supports the optimization of clinical treatment strategies.