Evaluation epidermal p53 immunostaining by digital image analysis - Brianezi, Gabrielli [UNESP]; Minicucci, Eliana Maria [UNESP]; Marques, Mariângela Esther Alencar [UNESP]; Miot, Hélio Amante [UNESP] (Wiley, 2013)
Digital techniques have been developed and validated to assess semiquantitatively immunohistochemical nuclear staining. Currently visual classification is the standard for qualitative nuclear evaluation. Analysis of pixels that represents the immunohistochemical labeling can be more sensitive, reproducible and objective than visual grading. This study compared two semiquantitative techniques of digital image analysis with three techniques of visual analysis imaging to estimate the p53 nuclear immunostaining. Methods: Sixty-three sun-exposed forearm-skin biopsies were photographed and submitted to three visual analyses of images: the qualitative visual evaluation method (0 to 4 +), the percentage of labeled nuclei and HSCORE. Digital image analysis was performed using ImageJ 1.45p; the density of nuclei was scored per ephitelial area (DensNU) and the pixel density was established in marked suprabasal epithelium (DensPSB). Results: Statistical significance was found in: the agreement and correlation among the visual estimates of evaluators, correlation among the median visual score of the evaluators, the HSCORE and the percentage of marked nuclei with the DensNU and DensPSB estimates. DensNU was strongly correlated to the percentage of p53-marked nuclei in the epidermis, and DensPSB with the HSCORE. Conclusion: The parameters presented herein can be applied in routine analysis of immunohistochemical nuclear staining of epidermis. © 2012 John Wiley & Sons A/S.
Keywords: Computer-assisted; Image cytometry; Image processing; Tumor suppressor protein p53; Computer assisted; Digital image analysis; Digital techniques; Immunostaining; Routine analysis; Statistical significance; Tumor suppressor proteins; Visual analysis; Visual classification; Visual estimate; Visual evaluation; Visual grading; Image analysis; Pixels; protein p53; digital image analysis; epidermis; evaluation; human; human tissue; image analysis; immunohistochemistry; parameters; skin biopsy; statistical significance; sun exposure; visual analog scale; Biopsy; Cell Nucleus; Epidermis; Forearm; Humans; Image Cytometry; Image Processing, Computer-Assisted; Immunohistochemistry; Photography; Sunlight; Tumor Suppressor Protein p53