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Analysis of Lymphomas by Flow Cytometry Current and Emerging Strategies
Author(s) -
BRAYLAN R. C.,
BENSON N. A.,
ITURRASPE J.
Publication year - 1993
Publication title -
annals of the new york academy of sciences
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.712
H-Index - 248
eISSN - 1749-6632
pISSN - 0077-8923
DOI - 10.1111/j.1749-6632.1993.tb38791.x
Subject(s) - flow cytometry , immunophenotyping , computer science , antigen , gating , computational biology , pattern recognition (psychology) , artificial intelligence , medicine , immunology , biology , neuroscience
The standard style for reporting results of immunophenotype analysis of lymphocytes by FCM is in the form of percentages of antigen-expressing cells. This procedure does not fully exploit the capabilities of FCM and is not always applicable to neoplastic samples. An alternative procedure for data analysis consists of a visual examination of the graphical displays of antibody binding patterns and size distribution without considering the actual fraction of fluorescent (positive) cells. Although it requires visual training and detailed examination of the data, this "pattern recognition" strategy offers unique diagnostic information that cannot be derived from simple percentages. Furthermore, the use of multiple labels, combined with interactive gating based on changes in cell size or intensity of antigen expression, provides high levels of sensitivity in detection of neoplastic cells and is an invaluable strategy in cases of minimal tumor involvement.