Abstract
Abstract 4724
Introduction
Differential white blood cell count (dWBC) is an important and frequently used diagnostic tool in Hematology. Automated blood counters produce a five-part differential count. If the five-part differential count does not meet pre-set criteria, microscopic dWBC is performed. This morphological based dWBC is labour intensive and requires intensive and sustained training of technicians. In addition to inter-observer variation, the statistical variation is significant. Offering reliable round the clock service for dWBC can be a logistic challenge, in particular in samples from patients with haematological disease.
Flowcytometry is a candidate reference method for dWBC. It has several advantages over morphological identification such as immunological definition of cell populations and high number of measured cells. Our goal was to develop a flowcytometric dWBC, called Leukoflow, which is easy to perform in a single tube, can be interpreted rapidly and can be available in a 24h/7d laboratory setting with a short turn around time.
Method
We selected 100 normal and 100 abnormal EDTA blood samples based on the data of the automated blood counter (LH750, Beckman Coulter) and the CLSI H20-A2 criteria. For flowcytometric dWBC, 20 ul EDTA blood is stained with an antibody cocktail (CD4, CD14, CD34, CD16, CD56, CD19, CD45, CD138, CD3 and CD71). Erythrocytes were lysed with ammonium chloride. Flowcount beads were added to determine the absolute concentrations of the cell populations in addition to their percentages. Flowcytometric analysis was performed using five channels on a FC500 (Beckman-Coulter). Using sequential gating, 13 cell populations were defined. For comparison, two independent technicians each counted 200 white blood cells. The data from Leukoflow are compared with the automated blood cell counter and the average from the two microscopical dWBCs.
Results
Leukoflow results correlate very well with both the automated blood cell counter and microscopic differentiation for leukocyte count as well as five-part differentiation. This applies for both normal and abnormal samples. Even without the use of positive markers for basophils or eosinophils, we could successfully define these populations by subtracting other positively defined populations in the regions where basophils and eosinophils are found in the CD45 SS staining.
Reproducibility experiments showed that Leukoflow differentiation performed better than both traditional dWBC techniques. For all populations, except the myeloid progenitors, the coefficients of variation (CV%) of Leukoflow were less than 5%. Myeloid left-shift is detected earlier by Leukoflow in the abnormal samples. Furthermore blast counts reported by Leukoflow suffer less from inter-observer variation compared to manual dWBC, and proved to be more relevant and fitting to the clinical diagnosis. The correlation for erytroblasts between an additional flowcytometric CD45 and DRAQ5 based staining, and microscopy was excellent (r=0,96). In addition to traditional dWBC-techniques, extra cell populations are determined by Leukoflow: T-lymphocytes, CD4-lymphocytes, B-lymphocytes, NK cells, myeloid progenitors, plasma cells and blasts. When blasts are present, the Leukoflow analysis also indicates if they are from B-cell (surface CD19) or T-cell (surface CD3) origin.
Conclusion
Accurate dWBC can be performed with Leukoflow. The assay requires a small amount of blood and can be performed round the clock. The additional cell populations determined by Leukoflow enable faster diagnosis and give useful clinical information. The large number of cells analysed, compared with standard dWBC techniques, favors detection of rare cell populations. Preliminary data revealed that Leukoflow can also be used for analysis of bone marrow samples. Ongoing studies are focussing on the additional clinical value of Leukoflow over traditional dWBCs. Leukoflow is a highly interesting technique to screen blood samples from patients with haematological diseases in clinical haematology laboratories.
Disclosures:
No relevant conflicts of interest to declare.
Automated classification of blood cell neutrophils.
