The human carcinogenicity evaluation of chemicals has a great impact on public health. In vitro methods, such as the cell transformation assay (CTA), allow for a fast and reliable assessment of the carcinogenic potential of a chemical compound in comparison with the standard two-year bioassay. The scoring and classification of foci in selected cell lines is performed, after staining, by light microscopy. Foci can be separated into three classes: type I, which are scored as non-transformed, and types II and III that are considered to include fully transformed foci. However, in a number of cases, even an expert is uncertain about the attribution of a focus to a given class, due to its mixed or intermediate nature. Here, we suggest a simple approach to classifying mixed or intermediate foci by exploiting the quantitative information available from images, which is captured by statistical descriptors. A quantitative index is proposed, to describe the degree of dissimilarity of mixed and intermediate images to the three well-distinguished classes.

The Cell Transformation Assay: Toward a Statistical Classification of Mixed and Intermediate Foci Images / C. Procaccianti, F.M. Stefanini, C. Urani. - In: ATLA. ALTERNATIVES TO LABORATORY ANIMALS. - ISSN 0261-1929. - 39(2011 Mar), pp. 23-36.

The Cell Transformation Assay: Toward a Statistical Classification of Mixed and Intermediate Foci Images

F.M. Stefanini
Secondo
;
2011

Abstract

The human carcinogenicity evaluation of chemicals has a great impact on public health. In vitro methods, such as the cell transformation assay (CTA), allow for a fast and reliable assessment of the carcinogenic potential of a chemical compound in comparison with the standard two-year bioassay. The scoring and classification of foci in selected cell lines is performed, after staining, by light microscopy. Foci can be separated into three classes: type I, which are scored as non-transformed, and types II and III that are considered to include fully transformed foci. However, in a number of cases, even an expert is uncertain about the attribution of a focus to a given class, due to its mixed or intermediate nature. Here, we suggest a simple approach to classifying mixed or intermediate foci by exploiting the quantitative information available from images, which is captured by statistical descriptors. A quantitative index is proposed, to describe the degree of dissimilarity of mixed and intermediate images to the three well-distinguished classes.
Settore SECS-S/01 - Statistica
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2434/849346
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