Near-infrared fluorescent digital pathology for the automation of disease diagnosis and biomarker assessment

近红外荧光数字病理学用于疾病诊断和生物标志物评估的自动化

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作者:Summer L Gibbs, Elizabeth Genega, Jeffery Salemi, Vida Kianzad, Haley L Goodwill, Yang Xie, Rafiou Oketokoun, Parmeshwar Khurd, Ali Kamen, John V Frangioni

Abstract

Hematoxylin-eosin (H&E) staining of tissue has been the mainstay of pathology for more than a century. However, the learning curve for H&E tissue interpretation is long, whereas intra- and interobserver variability remain high. Computer-assisted image analysis of H&E sections holds promise for increased throughput and decreased variability but has yet to demonstrate significant improvement in diagnostic accuracy. Addition of biomarkers to H&E staining can improve diagnostic accuracy; however, coregistration of immunohistochemical staining with H&E is problematic as immunostaining is completed on slides that are at best 4 μm apart. Simultaneous H&E and immunostaining would alleviate coregistration problems; however, current opaque pigments used for immunostaining obscure H&E. In this study, we demonstrate that diagnostic information provided by two or more independent wavelengths of near-infrared (NIR) fluorescence leave the H&E stain unchanged while enabling computer-assisted diagnosis and assessment of human disease. Using prostate cancer as a model system, we introduce NIR digital pathology and demonstrate its utility along the spectrum from prostate biopsy to whole mount analysis of H&E-stained tissue.

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