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1. The cell trasformation assay: Toward a statistical classification of mixed and intermediate foci images

Author

Procaccianti, C, Stefanini, F, Urani, C, Stefanini, FM, Urani, C., Procaccianti, C, Stefanini, F, Urani, C, Stefanini, FM, and Urani, C.

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

Published
2011

2. The cell trasformation assay: Toward a statistical classification of mixed and intermediate foci images

Author

Federico M. Stefanini, C. Procaccianti, Chiara Urani, Procaccianti, C, Stefanini, F, and Urani, C

Subjects
quantitative morphology, Focus (geometry), Computer science, Carcinogenicity Tests, Quantitative morphology, Toxicology, Animal Testing Alternatives, General Biochemistry, Genetics and Molecular Biology, Mice, in vitro cell trasformation, Image Processing, Computer-Assisted, cluster analysi, Animals, Cluster Analysis, Neoplastic transformation, Statistical descriptors, BIO/06 - ANATOMIA COMPARATA E CITOLOGIA, Alternative methods, Microscopy, business.industry, Pattern recognition, General Medicine, chemical carcinogenesi, Medical Laboratory Technology, Statistical classification, Transformation (function), Cell Transformation, Neoplastic, Artificial intelligence, business
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.

Published
2011

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