ABSTRACT
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.
Subject(s)
Bleomycin , Laminin , Pulmonary Fibrosis , Laminin/metabolism , Animals , Pulmonary Fibrosis/pathology , Pulmonary Fibrosis/metabolism , Pulmonary Fibrosis/chemically induced , Lung/pathology , Lung/metabolism , Mice , Lung Injury/pathology , Lung Injury/metabolism , Lung Injury/chemically induced , Disease Models, Animal , Mice, Inbred C57BL , Tertiary Lymphoid Structures/pathology , Tertiary Lymphoid Structures/immunology , Humans , Fluorescent Antibody Technique , Extracellular Matrix/metabolism , Extracellular Matrix/pathologyABSTRACT
Investigations into the mechanisms of injury and repair in pulmonary fibrosis require consideration of the spatial heterogeneity inherent in the disease. Most scoring of fibrotic remodeling in preclinical animal models rely on the modified Ashcroft score, which is a semi-quantitative scoring rubric of macroscopic resolution. The obvious limitations inherent in manual pathohistological grading have generated an unmet need for unbiased, repeatable scoring of fibroproliferative burden in tissue. Using computer vision approaches on immunofluorescent imaging of the extracellular matrix (ECM) component laminin, we generate a robust and repeatable quantitative remodeling scorer (QRS). In the bleomycin lung injury model, QRS shows significant agreement with modified Ashcroft scoring with a significant Spearman coefficient r=0.768. This antibody-based approach is easily integrated into larger multiplex immunofluorescent experiments, which we demonstrate by testing the spatial apposition of tertiary lymphoid structures (TLS) to fibroproliferative tissue. The tool reported in this manuscript is available as a standalone application which is usable without programming knowledge.
