[Hematological analysis of leukemic diseases using an automated hematology analyzer]. 1993

H Shigeta
Clinical Laboratory Division, Chiba Cancer Center Hospital.

Owing to recent technical developments in automated hematology analyzers, identification of 5-part differential counts in white blood cells and also of abnormal leukocytes has become possible. Blood specimens from 200 patients with leukemic hematologic conditions were processed through a Coulter STKS which gives a favorable white cell differential count utilizing the following parameters: volumetric impedance (V), electric conductivity/cell volume (C), and a monochromatic laser beam which provides collectively white cell scatterplot (S). To analyze the presented figures of a pathologic scatterplot (SP) on the visual display unit, the standard scale derived from 220 normal SP patterns which was composed of four kinds of cell SP scales (neutrophil: N, monocyte: Mo, eosinophil: Eo, lymphocyte: Ly) was applied. Leukemic SP figures were variable depending upon both the type of FAB classification and their therapeutic processes. SP forms of M0-blasts were semi-round and located in the central area surrounded by N-, Mo-, and Ly-SP scale. Blast SP of M1 and M2 was shown as a developing process to the SP field containing immature myeloid cells extending from the central area. It was reasonable that immature neutrophilic SP expression was obtained in M3 and Ph1 positive CML. However, the SP of M3v and Ph1 negative CML showed myelomonocytic features as CMMoL does. Typical myelomonocytic SP patterns were obtained in M4 patients. SP figures of MDS were characterized by deformability, dislocation and another abnormality, and these changes, especially in lymphocytes are very useful for diagnosis of MDS. Therefore, the FAB subtype of AML including MDS and CML could be distinguished from each other on the basis of SP pattern. In lymphoproliferative disorders, limited conductivity in ALL-SP was characteristic, while irregular and deformed SP was peculiar in leukemic malignant lymphoma. It would be a valuable process to analyze the SP pattern obtained from an automated hematology analyzer for identification of leukemic diseases.

UI MeSH Term Description Entries
D007938 Leukemia A progressive, malignant disease of the blood-forming organs, characterized by distorted proliferation and development of leukocytes and their precursors in the blood and bone marrow. Leukemias were originally termed acute or chronic based on life expectancy but now are classified according to cellular maturity. Acute leukemias consist of predominately immature cells; chronic leukemias are composed of more mature cells. (From The Merck Manual, 2006) Leucocythaemia,Leucocythemia,Leucocythaemias,Leucocythemias,Leukemias
D007958 Leukocyte Count The number of WHITE BLOOD CELLS per unit volume in venous BLOOD. A differential leukocyte count measures the relative numbers of the different types of white cells. Blood Cell Count, White,Differential Leukocyte Count,Leukocyte Count, Differential,Leukocyte Number,White Blood Cell Count,Count, Differential Leukocyte,Count, Leukocyte,Counts, Differential Leukocyte,Counts, Leukocyte,Differential Leukocyte Counts,Leukocyte Counts,Leukocyte Counts, Differential,Leukocyte Numbers,Number, Leukocyte,Numbers, Leukocyte
D001772 Blood Cell Count The number of LEUKOCYTES and ERYTHROCYTES per unit volume in a sample of venous BLOOD. A complete blood count (CBC) also includes measurement of the HEMOGLOBIN; HEMATOCRIT; and ERYTHROCYTE INDICES. Blood Cell Number,Blood Count, Complete,Blood Cell Counts,Blood Cell Numbers,Blood Counts, Complete,Complete Blood Count,Complete Blood Counts,Count, Blood Cell,Count, Complete Blood,Counts, Blood Cell,Counts, Complete Blood,Number, Blood Cell,Numbers, Blood Cell
D006801 Humans Members of the species Homo sapiens. Homo sapiens,Man (Taxonomy),Human,Man, Modern,Modern Man
D001322 Autoanalysis Method of analyzing chemicals using automation. Autoanalyses

Related Publications

H Shigeta
January 2007, Rinsho byori. The Japanese journal of clinical pathology,
H Shigeta
April 2005, Indian journal of pathology & microbiology,
H Shigeta
June 2003, Rinsho byori. The Japanese journal of clinical pathology,
H Shigeta
September 2014, Veterinary journal (London, England : 1997),
H Shigeta
June 2003, Rinsho byori. The Japanese journal of clinical pathology,
H Shigeta
November 2016, Rinsho byori. The Japanese journal of clinical pathology,
H Shigeta
August 2019, International journal of hematology,
H Shigeta
August 1996, Rinsho byori. The Japanese journal of clinical pathology,
Copied contents to your clipboard!