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

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

Research output: Contribution to journalArticle

3 Citations (Scopus)

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.

Original languageEnglish (US)
JournalMolecular Imaging
Volume14
Issue number4
DOIs
StatePublished - Jun 1 2015
Externally publishedYes

Fingerprint

biomarkers
Automation
pathology
Biomarkers
Pathology
staining
automation
Tissue
Staining and Labeling
Infrared radiation
Computer-Assisted Diagnosis
learning curves
Learning Curve
Observer Variation
Computer-Assisted Image Processing
Biopsy
Hematoxylin
Eosine Yellowish-(YS)
pigments
image analysis

ASJC Scopus subject areas

  • Radiology Nuclear Medicine and imaging
  • Biotechnology
  • Molecular Medicine
  • Biomedical Engineering
  • Condensed Matter Physics

Cite this

Near-infrared fluorescent digital pathology for the automation of disease diagnosis and biomarker assessment. / Gibbs, Summer; Genega, Elizabeth; Salemi, Jeffery; Kianzad, Vida; Goodwill, Haley L.; Xie, Yang; Oketokoun, Rafiou; Khurd, Parmeshwar; Kamen, Ali; Frangioni, John V.

In: Molecular Imaging, Vol. 14, No. 4, 01.06.2015.

Research output: Contribution to journalArticle

Gibbs, S, Genega, E, Salemi, J, Kianzad, V, Goodwill, HL, Xie, Y, Oketokoun, R, Khurd, P, Kamen, A & Frangioni, JV 2015, 'Near-infrared fluorescent digital pathology for the automation of disease diagnosis and biomarker assessment', Molecular Imaging, vol. 14, no. 4. https://doi.org/10.2310/7290.2015.00005
Gibbs, Summer ; Genega, Elizabeth ; Salemi, Jeffery ; Kianzad, Vida ; Goodwill, Haley L. ; Xie, Yang ; Oketokoun, Rafiou ; Khurd, Parmeshwar ; Kamen, Ali ; Frangioni, John V. / Near-infrared fluorescent digital pathology for the automation of disease diagnosis and biomarker assessment. In: Molecular Imaging. 2015 ; Vol. 14, No. 4.
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