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Jornal Brasileiro de Patologia e Medicina Laboratorial
Print version ISSN 1676-2444
On-line version ISSN 1678-4774
BRIANEZI, Gabrielli; CAMARGO, João Lauro Viana de and MIOT, Hélio Amante. Development and validation of a quantitative image analysis method to evaluate comet assay (silver staining). J. Bras. Patol. Med. Lab. [online]. 2009, vol.45, n.4, pp.325-334. ISSN 1676-2444. http://dx.doi.org/10.1590/S1676-24442009000400010.
BACKGROUND: Comet assay or single cell gel electrophoresis is a useful and widely applied technique for the assessment of DNA damage and repair in individual cells. Nuclei can be stained with fluorescence methods or silver salts. The latter has technical advantages such as the type of microscope used and the possibility of slide storage. Comet analysis may be performed visually, however, there is the disadvantage of subjective results, which can be minimized by automated digital analysis. OBJECTIVES: Development and validation of digital analysis method for silver stained comet assays. METHODS: Fifty comets were photographed in a standardized way and printed on paper. Before and after being automatically preprocessed by ImageJ 1.38x software, the images were manually measured and classified into five categories by three evaluators. Their estimates were compared as to their correlation and reproducibility. Afterwards, an algorithm for automated digital analysis of the comet measurements was developed based on statistical filters of median and minimum. These results were compared with those manually and visually estimated after preprocessing. RESULTS: Manual measurements of preprocessed images showed higher intraclass correlation than the original ones. Automated results had high correlation with the pre-processed manual measurements, suggesting that this system increases objectivity and can be used in the estimation of comet parameters. CONCLUSIONS: Digital analysis of silver stained comet assay proved to be feasible and better reproducible than the visual analysis.
Keywords : Comet assay; Genotoxicity; Image analysis; Quantitative method.