Comparison of automated and manual techniques for analysis of DNA frequency distributions in bladder washings

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Abstract
Quantitative methods for interpretation of flow cytometry DNA histograms are required for the widespread clinical use of this technology. The usefulness of a histogram analysis technique in this setting requires that it be operator independent, easy to implement in a clinical laboratory, and provide high sensitivity to the desired information. Additionally, the technique must be tolerant to the relatively low signal‐to‐noise ratios often found in DNA distributions obtained from clinical samples. Among the factors that have been used to assess the malignant potential of tumors are the presence of an aneuploid population, the proportion of hyperdiploid cells, the width of the G1 peak, the DNA index, and the fraction of cells in S. A computer‐based method has been developed for extraction of the above‐mentioned features from DNA histograms. The program detects peaks in the histogram and uses straight‐line fits to the cumulative frequency distribution to define cell population bounds. A test set of 44 histograms compiled from bladder irrigation specimens obtained from patients with a present or past history of transitional cell carcinoma (TCC) was analyzed by five collaborating laboratories forming a Network sponsored by the National Cancer Institute (NCI). This test set was used to evaluate the performance of the computer‐based method by comparing results with those of four expert observers. In this preliminary analysis, perfect agreement was found in the detection of aneuploid cell populations by all observers and the computer‐based method. Correlation of percent hyperdiploid cell fraction was also excellent. This computer‐based method for the analysis of DNA frequency distributions should have utility in the establishment of DNA flow cytometry of bladder irrigation specimens as a useful and routine laboratory procedure.