Investigations into the mechanisms of injury and repair in fibroproliferative disease require consideration of the spatial heterogeneity inherent in the disease. Most scoring of fibrotic remodeling in preclinical animal models relies on the modified Ashcroft score, which is an ordinal rubric of macroscopic resolution. The obvious limitations of manual histopathologic scoring have generated an unmet need for unbiased, repeatable scoring of fibroproliferative burden in tissue. Using computer vision approaches on immunofluorescence imaging of the extracellular matrix component laminin, we generated a robust and repeatable quantitative remodeling scorer. In the bleomycin lung injury model, the quantitative remodeling scorer shows significant agreement with the modified Ashcroft scale. This antibody-based approach is easily integrated into larger multiplex immunofluorescence experiments, which we demonstrate by testing the spatial apposition of tertiary lymphoid structures to fibroproliferative tissue, a poorly characterized phenomenon observed in both human interstitial lung diseases and preclinical models of lung fibrosis. The tool reported in this article is available as a stand-alone application that is usable without programming knowledge.
Keywords: Fibrosis; histology; histopathology; imaging.