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Open Access Research

Long-term analysis to objectify the tumour grading by means of automated microscopic image analysis of the nucleolar organizer regions (AgNORs) in the case of breast carcinoma

Klaus-Jürgen Winzer1*, Joachim Bellach2 and Peter Hufnagl3

Author Affiliations

1 Clinic for Gynaecology – Breast Center, Berlin, Germany

2 Comprehensive Cancer Center Charité, Berlin, Germany

3 Institute of Pathology, Charité - Universitätsmedizin Berlin, Charité-Platz 1, Berlin, 10117, Germany

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Diagnostic Pathology 2013, 8:56  doi:10.1186/1746-1596-8-56

Published: 8 April 2013

Abstract

Background

Apart from a number of cases of inaccurate prognosis in regard to individual patients, the inter- and intra-observer variability of the classical, histological prognosis parameters have been under repeated discussion. For this reason, a long-term analysis was carried out in regard to overall survival by means of automated microscopic image analysis of the nucleolar organizer regions (AgNORs) to objectify tumour grading in the case of breast carcinoma.

This consists of a selective representation of argyrophilic proteins that are associated with the nucleolus organising regions.

Methods

The evaluation included 244 female patients with an average age of 59.3 years. The characterisation of the histological sections was carried out on the basis of the AMBA/R system. With this software the histometric characterisation level was evaluated in terms of the nucleolus organizer regions. The post-observation data were obtained from the clinical register and were complemented by mortality data from the cancer registers and by data supplied by the residents’ registration office of Berlin.

Results

The average post-observation period was 106.6 months. With the Cox-Regression the influence of the co-variables (conventional prognosis parameters and AgNOR parameters) were examined. In the model, only the parameters pN, G and various AgNOR parameters remain present.

Conclusion

There is a strong correlation between survival and selected AgNOR parameters. These could replace the conventional grading as the standard measure for the mitosis rate together with the pleomorphism level. Instead of the-time consuming AMBA/R system originally used, a new implementation of AgNOR quantification with modern VM systems could be applied.

Virtual slides

The virtual slide(s) for this article can be found here: http://www.diagnosticpathology.diagnomx.eu/vs/1449591192859058 webcite.

Keywords:
Breast cancer; Grading; Image analysis; AgNOR quantification; Survival analysis; Cox regression