Abstract
Pulmonary fibrosis is characterized by abnormal interstitial extracellular matrix and cellular accumulations. Methods quantifying fibrosis severity in lung histopathology samples are semi-quantitative, subjective, and analyze only portions of sections. We sought to determine whether automated computerized imaging analysis shown to continuously measure fibrosis in mice could also be applied in human samples. A pilot study was conducted to analyze a small number of specimens from patients with Hermansky-Pudlak syndrome pulmonary fibrosis (HPSPF) or idiopathic pulmonary fibrosis (IPF). Digital images of entire lung histological serial sections stained with picrosirius red and alcian blue or anti-CD68 antibody were analyzed using dedicated software to automatically quantify fibrosis, collagen, and macrophage content. Automated fibrosis quantification based on parenchymal tissue density and fibrosis score measurements was compared to pulmonary function values or Ashcroft score. Automated fibrosis quantification of HPSPF lung explants was significantly higher than that of IPF lung explants or biopsies and was also significantly higher in IPF lung explants than in IPF biopsies. A high correlation coefficient was found between some automated quantification measurements and lung function values for the three sample groups. Automated quantification of collagen content in lung sections used for digital image analyses was similar in the three groups. CD68 immunolabeled cell measurements were significantly higher in HPSPF explants than in IPF biopsies. In conclusion, computerized image analysis provides access to accurate, reader-independent pulmonary fibrosis quantification in human histopathology samples. Fibrosis, collagen content, and immunostained cells can be automatically and individually quantified from serial sections. Robust automated digital image analysis of human lung samples enhances the available tools to quantify and study fibrotic lung disease.
Highlights
Pulmonary fibrosis is a chronic interstitial lung disease (ILD) characterized by alveolar parenchymal accumulation of extracellular matrix protein, mesenchymal cells, and immune cells that disrupts normal lung architecture [1]
We developed an automated software program which meets these criteria using a murine model of bleomycininduced pulmonary fibrosis [29]. We explored whether this software program could quantify fibrosis in a small number of human lung tissue specimens obtained from Hermansky-Pudlak syndrome (HPS) pulmonary fibrosis and idiopathic pulmonary fibrosis (IPF) patients and biopsies from IPF patients
We show that the automated digital quantification we developed in the present study for assessment of pulmonary fibrosis in human lung specimens from patients with HPS or IPF is advantageous because this method provides accurate, reliable and reader-independent continuous measurements of fibrosis severity in entire lung tissue sections
Summary
Pulmonary fibrosis is a chronic interstitial lung disease (ILD) characterized by alveolar parenchymal accumulation of extracellular matrix protein, mesenchymal cells, and immune cells that disrupts normal lung architecture [1]. Reported in 1988, Ashcroft scoring of lung tissue continues to be utilized as a method to quantify severity of pulmonary fibrosis in stained histologic sections [20]. It is possible that assessment of fibrosis from random fields may inadvertently overestimate or underestimate the degree of fibrosis in the entire lung section Given these limitations, there is a need to develop a quantitative, accurate, rapid, and reader-independent assessment of pulmonary fibrosis severity in entire tissue sections. We show that this digital histological analysis of pulmonary fibrosis can be readily applied to human samples, and further studies with a larger sample size are indicated This tool provides robust, accurate, reader-independent quantification of pulmonary fibrosis and enhances the available methods to study fibrotic lung disease
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