Literature DB >> 19289554

Image analysis algorithms for immunohistochemical assessment of cell death events and fibrosis in tissue sections.

Maryla Krajewska1, Layton H Smith, Juan Rong, Xianshu Huang, Marc L Hyer, Nikolajs Zeps, Barry Iacopetta, Steven P Linke, Allen H Olson, John C Reed, Stan Krajewski.   

Abstract

Cell death is of broad physiological and pathological importance, making quantification of biochemical events associated with cell demise a high priority for experimental pathology. Fibrosis is a common consequence of tissue injury involving necrotic cell death. Using tissue specimens from experimental mouse models of traumatic brain injury, cardiac fibrosis, and cancer, as well as human tumor specimens assembled in tissue microarray (TMA) format, we undertook computer-assisted quantification of specific immunohistochemical and histological parameters that characterize processes associated with cell death. In this study, we demonstrated the utility of image analysis algorithms for color deconvolution, colocalization, and nuclear morphometry to characterize cell death events in tissue specimens: (a) subjected to immunostaining for detecting cleaved caspase-3, cleaved poly(ADP-ribose)-polymerase, cleaved lamin-A, phosphorylated histone H2AX, and Bcl-2; (b) analyzed by terminal deoxyribonucleotidyl transferase-mediated dUTP nick end labeling assay to detect DNA fragmentation; and (c) evaluated with Masson's trichrome staining. We developed novel algorithm-based scoring methods and validated them using TMAs as a high-throughput format. The proposed computer-assisted scoring methods for digital images by brightfield microscopy permit linear quantification of immunohistochemical and histochemical stainings. Examples are provided of digital image analysis performed in automated or semiautomated fashion for successful quantification of molecular events associated with cell death in tissue sections.

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Year:  2009        PMID: 19289554      PMCID: PMC2699321          DOI: 10.1369/jhc.2009.952812

Source DB:  PubMed          Journal:  J Histochem Cytochem        ISSN: 0022-1554            Impact factor:   2.479


  40 in total

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  42 in total

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