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 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 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.

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