Assessment of the Analytical Performances of the Flow Leucocyte Differential Method

Abstract 4727

The examination of blood films by microscopy remains one of the major labour intensive procedures in the laboratory and the challenge is to reduce the number of blood films examined without missing important diagnostic information. Automated blood cell counters offer a leucocyte count, red cell and platelet count and five-part (some 6-part) leucocyte differential. Haematology instrument differentials provide only limited information on cell morphology using abnormal cell flags and are often unable to reliably classify abnormal and immature cells.

The examination of blood films is not only time consuming, it also requires highly trained staff. The impact of a wrong diagnosis necessitates that experienced staff are present in the laboratory 24 hours a day. Furthermore, manual cell classification is subjective, with significant inter and intra observer variation (Koepke et al. 1985) and is also subject to significant statistical variance (Rumke 1985).

There have recently been several reports of using monoclonal antibody cocktails for an extended leucocyte differential by flow cytometry (Faucher et al. 2007, Roussel et al. 2010). The aim of this study was to compare a flow cytometric method for the white blood cell differential with the automated count from the Beckman Coulter LH750 haematology analyser and the reference manual microscopic 2 × 200 cell count (CLSI H20-A2). Cell morphology was also assessed microscopically for the presence of cells such as reactive or abnormal lymphocytes or blasts. The flow cytometric method, described by Faucher et al. 2007, uses 6 antibodies (CD45, CD36, CD2, CD294, CD19 and CD16) premixed in a single tube. The protocol allows detection of all white blood cells, mature neutrophils, total lymphocytes, total monocytes, eosinophils, basophils, immature granulocytes, B lymphocytes, non-cytotoxic T-lymphocytes, cytotoxic T/NK lymphocytes, CD16 positive and CD16 negative monocytes, and blasts cells with lineage orientation. A 5-colour flow cytometer, the Beckman Coulter FC500, was used for analysis. The gating strategy described by Faucher et al. (2007) was used.

EDTA blood was analysed on 27 normal samples and 148 abnormal samples which demonstrated abnormal cell flags on the LH750. These samples included the presence of blast cells, immature granulocytes and abnormal lymphocytes.

Results for most cell populations measured by the flow cytometric differential compared well with both the LH750 automated differential and the manual reference method. Comparative results using Pearson correlation show that the automated LH750 differential produced r values of greater than 0.94 for neutrophils, lymphocytes and eosinophils. The manual reference method produced r values of greater than 0.89 for neutrophils, lymphocytes and eosinophils. Results for flow cytometric monocytes compared to the LH750 and manual differential gave an r value of 0.84 and 0.87 respectively. Results for basophils were significantly better when the flow cytometric method was compared to the LH750 rather than the manual method, r = 0.68 for flow cytometry versus LH750 and r = 0.43 for flow cytometry versus manual method. The value of the manual differential is diminished because of the low number of cells counted; the precision is not good for smaller cell populations (Hübl et al. 1995). Very good correlation of blast cells, r = 0.98 and immature granulocytes, r = 0.92 was seen between the manual and flow cytometric method.

The flow cytometric differential is superior to the microscopic method since it is objective and due to the higher number of cells counted, it can detect subpopulations of cells that are present in smaller number with greater statistical and interpretive confidence. More importantly, it recognises and quantitates morphologically abnormal cells such as reactive lymphocytes, inflammatory monocytes and the lineage of blast cells. However, the examination of blood cell morphology by microscopy still has an important role in the diagnosis of diseases.