Literature DB >> 22672779

Evaluation epidermal p53 immunostaining by digital image analysis.

Gabrielli Brianezi1, Eliana Maria Minicucci, Mariângela Esther Alencar Marques, Hélio Amante Miot.   

Abstract

BACKGROUND/
PURPOSE: 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.

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Year:  2012        PMID: 22672779     DOI: 10.1111/j.1600-0846.2012.00616.x

Source DB:  PubMed          Journal:  Skin Res Technol        ISSN: 0909-752X            Impact factor:   2.365


  3 in total

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Authors:  Carlijn A M Roumans; Manon C W Spaander; Iris Lansdorp-Vogelaar; Katharina Biermann; Marco J Bruno; Ewout W Steyerberg; Dimitris Rizopoulos
Journal:  PLoS One       Date:  2022-04-27       Impact factor: 3.752

2.  Dermal type I collagen assessment by digital image analysis.

Authors:  Gabrielli Brianezi; Fabrizio Grandi; Ediléia Bagatin; Mílvia Maria S S Enokihara; Hélio Amante Miot
Journal:  An Bras Dermatol       Date:  2015 Sep-Oct       Impact factor: 1.896

3. 

Authors:  Hélio Amante Miot
Journal:  J Vasc Bras       Date:  2016 Apr-Jun
  3 in total

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