Near-Infrared Fluorescent Digital Pathology for the Automation of Disease Diagnosis and Biomarker Assessment
Author(s) -
Summer L. Gibbs,
Elizabeth M. Genega,
Jeffery Salemi,
Vida Kianzad,
Haley L. Goodwill,
Yang Xie,
Rafiou Oketokoun,
Parmeshwar Khurd,
Ali Kamen,
John V. Frangioni
Publication year - 2015
Publication title -
molecular imaging
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.815
H-Index - 60
eISSN - 1536-0121
pISSN - 1535-3508
DOI - 10.2310/7290.2015.00005
Subject(s) - biomarker , pathology , medicine , digital pathology , fluorescence , computational biology , biology , biochemistry , optics , physics
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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