Literature DB >> 8536414

An assessment of the Coulter VCS automated differential counter scatterplots in the recognition of specific acute leukaemia variants.

A R Pettitt1, P Grace, P Chu.   

Abstract

The Coulter VCS is an automated differential counter, which derives a five-part differential count on the basis of differences in cell volume, high frequency conductivity and light scatter. A printed scatterplot relating volume and scatter is readily obtained. Other instruments which use automated cytochemistry can distinguish between AML and ALL, and between AML variants. It was our impression that the Coulter VCS might also be capable of such distinction on the basis of the scatterplot patterns. We therefore collected scatterplots produced by Coulter VCS analysis of peripheral blood from 63 patients presenting with acute leukaemia. The scatterplots were inspected and six basic patterns identified. The scatterplots were inspected and six basic patterns identified. The scatterplots could be reproducibly sorted into pattern-specific groups without knowledge of the diagnosis. Precise leukaemic diagnoses were made routinely by conventional morphology, cytochemistry and immunophenotyping. A comparison was then made with the scatterplot patterns. The 51 cases of AML produced examples of all six patterns. The nine cases of ALL produced only three patterns. These were shared with cases of AML, and two were also shared with the three cases of acute mixed lineage leukaemia. Thus, three of the six patterns were specific for AML, whereas no pattern was specific for ALL or acute mixed lineage acute leukaemia. One pattern was produced only by the three cases of AML M6, and another was produced only by five of the 25 cases of primitive (M0 and M1) AML.(ABSTRACT TRUNCATED AT 250 WORDS)

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Mesh:

Year:  1995        PMID: 8536414

Source DB:  PubMed          Journal:  Clin Lab Haematol        ISSN: 0141-9854


  1 in total

1.  Utility of cell population data (VCS parameters) as a rapid screening tool for Acute Myeloid Leukemia (AML) in resource-constrained laboratories.

Authors:  Harpreet Virk; Neelam Varma; Shano Naseem; Ishwar Bihana; Dmitry Sukhachev
Journal:  J Clin Lab Anal       Date:  2018-09-29       Impact factor: 2.352

  1 in total

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