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Analytical Cellular Pathology
Volume 25, Issue 3, Pages 147-153
http://dx.doi.org/10.1155/2003/410239

Correlation of Grade of Urothelial Cell Carcinomas and DNA Histogram Features Assessed by Flow Cytometry and Automated Image Cytometry

Marco G. W. Bol,1 Jan P. A. Baak,1,2 Bianca v. Diermen,1 E. A. M. Janssen,1 Susanne B. K. Buhr-Wildhagen,1 and Kjell-Henning Kjellevold1

1Department of Pathology, SIR Hospital, Stavanger, Norway
2Free University, Amsterdam, The Netherlands

Received 10 June 2002; Accepted 3 March 2003

Copyright © 2003 Hindawi Publishing Corporation. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Objective: To analyse how DNA ploidy and S-phase fraction (SPF) by flow cytometry (FCM) and an optimised fully automatic DNA image cytometer (ICM) correlate with grade in TaT1 urothelial cell carcinomas (UC) of the urinary bladder. Materials and methods: Two-hundred-and twenty-eight consensus cases were analysed. Single cell suspensions were stained (DAPI for FCM, Feulgen for ICM). There was enough material for both FCMand ICMin 202 of these cases. FCMand optimised ICM measurements were performed on the 202 UCs. To discriminate between different grades, single- and multivariate analyses was performed on DNA histogram features obtained with the MultiCycle program (using DNA index (DI) and SPF). Results: Overall measurement time of the adapted ICM method was 10.7 minutes per case (range 5.9–29.8 min.) and required little additional interactive object rejection (average 152 objects (84–298) on 3000 objects per case measured, which took 9.9 minutes on average, range 8.3–15.5 minutes). The ICM histograms looked much “cleaner” with less noise than the FCM graphs. The coefficient of variation (CV) of the diploid peak for ICM(5.4%) was significantly lower than for FCM(5.9%) (p < 0.0001). ICM features were more strongly correlated to grade than FCMfeatures. In multivariate analysis, the best discriminating set of features was DNA ploidy and SPF (both by ICM). Conclusions: The adapted fully automated DNA ICM works very well for UCs. Low CV DNA ICM histograms are obtained in a time comparable to FCM. The DNA ICM results have stronger discriminative power than DNA FCM for grade in TaT1 UCs. Colour figures can be viewed on http://www.esacp.org/acp/2003/25-3/bol.htm.