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Mod Pathol ; 2(5): 463-7, 1989 Sep.
Article in English | MEDLINE | ID: mdl-2813345

ABSTRACT

Quantitative analysis of cellular DNA content may be clinically useful for several solid tumors. The technology for this analysis by flow cytometry or image analysis has existed for several years but has not been widely used, except in a handful of specialized research institutions. Recently, however, relatively inexpensive image analyzers intended for use by hospital pathologists have been introduced that can analyze DNA content from cytology or imprint specimens which are readily obtainable from solid tumors. We report here an assessment of this technology for analysis of tumor imprint specimens, using flow cytometry of tissue blocks as the standard for comparison. We used image analysis equipment on Feulgan-stained imprint preparations from 31 tumors and compared the histograms with those obtained by flow cytometric analysis of archival tissue blocks from the same tumors. The ploidy descriptors (diploid, tetraploid, and aneuploid) were concordant for the two methods in 27 specimens, with three specimens yielding discordant results and one specimen considered unevaluable by image analysis. The image analysis method using imprints appeared to have several advantages over flow cytometry, including lower instrument cost, no need to dissociate paraffin blocks or fresh tissue, and ability to analyze very small samples. Somewhat lower resolution of the histograms, extremely localized tissue sampling, and possibly greater risk of occasionally obtaining unevaluable preparations were disadvantages. Microcomputer-based image analysis performed on imprints appeared to be a viable alternative to flow cytometric analysis of tissue blocks for quantitative DNA analysis of tumor specimens.


Subject(s)
Aneuploidy , DNA, Neoplasm/genetics , Diploidy , Flow Cytometry , Image Processing, Computer-Assisted , Neoplasms/genetics , Biomarkers, Tumor/genetics , Breast Neoplasms/genetics , Colonic Neoplasms/genetics , Flow Cytometry/economics , Humans , Image Processing, Computer-Assisted/economics , Lung Neoplasms/genetics
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