Background:Leukocyte differentials are an important component of clinical care. Morphologic assessment of peripheral blood smears (PBS) may be required to accurately classify leukocytes. However, manual microscopy is labor intensive. The CellaVision DM96 is an automated system that acquires digital images of leukocytes on PBS, pre-classifies the cell type, and displays them on screen for a Technologist or Pathologist to approve or reclassify. Our study compares the results of the DM96 with manual microscopy.Methods:Three hundred and fifty-nine PBS were selected and assessed by manual microscopy with a 200 leukocyte cell count. They were then reassessed using the CellaVision DM96 with a 115 leukocyte cell count including reclassification when necessary. Correlation between the manual microscopy results and the CellaVision DM96 results was calculated for each cell type.Results:The correlation coefficients (r2) range from a high of 0.99 for blasts to a low of 0.72 for metamyelocytes.Conclusions:The correlation between the CellaVision DM96 and manual microscopy was as good or better than the previously published data. The accuracy of leukocyte classification depended on the cell type, and in general, there was lower correlation for rare cell types. However, the correlation is similar to previous studies on the correlation of manual microscopy with an established reference result. Therefore, the CellaVision DM96 is appropriate for clinical implementation.

Background:Red blood cell (RBC) analysis is a key feature in the evaluation of hematological disorders. The gold standard light microscopy technique has high sensitivity, but is a relativity time-consuming and labor intensive procedure. This study tested the sensitivity and specificity of gold standard light microscopy manual differential to the CellaVision® DM96 (CCS; CellaVision, Lund, Sweden) automated image analysis system, which takes digital images of samples at high magnification and compares these images with an artificial neural network based on a database of cells and preclassified according to RBC morphology.Methods:In this study, 212 abnormal peripheral blood smears within the Calgary Laboratory Services network of hospital laboratories were selected and assessed for 15 different RBC morphologic abnormalities by manual microscopy. The same samples were reassessed as a manual addition from the instrument screen using the CellaVision® DM96 system with 8 microscope high power fields (×100 objective and a 22 mm ocular). The results of the investigation were then used to calculate the sensitivity and specificity of the CellaVision® DM96 system in reference to light microscopy.Results:The sensitivity ranged from a low of 33% (RBC agglutination) to a high of 100% (sickle cells, stomatocytes). The remainder of the RBC abnormalities tested somewhere between these two extremes. The specificity ranged from 84% (schistocytes) to 99.5% (sickle cells, stomatocytes).Conclusions:Our results showed generally high specificities but variable sensitivities for RBC morphologic abnormalities.

Introduction:Rapid and accurate determination of platelet count is an important factor in diagnostic medicine. Traditional microscopic methods are labor intensive with variable results and are highly dependent on the individual training. Recent developments in automated peripheral blood differentials using a computerized system have shown many advantages as a viable alternative. The purpose of this paper was to determine the reliability and accuracy of the CellaVision DM 96 system with regards to platelet counts.Materials and Methods:One hundred twenty seven peripheral blood smears were analyzed for platelet count by manual microscopy, an automated hematology analyzer (Beckman Counter LH 780 or Unicel DXH 800 analyzers) and with the CellaVision DM96 system. Results were compared using the correlations and Bland-Altman plots.Results:Platelet counts from the DM96 system showed an R2 of 0.94 when compared to manual platelet estimates and an R2 of 0.92 when compared to the automated hematology analyzer results. Bland-Altman plots did not show any systematic bias.

Context:Many hematology laboratories have adopted semi-automated digital platforms for routine use and the evidence supporting their use is increasing.Aims:The CellaVision platforms are among the most thoroughly studied digital hematology platforms; we wished to determine the accuracy of CellaVision for reticulocyte counting.Design, Materials and Methods:We compared reticulocyte counts performed manually, using the Beckman Coulter LH750 automated analyzer and with the CellaVision DM96 platform. We analyzed the results for pair-wise correlation and bias, and precision.Statistical Analyses Used:Analyses were performed using Statistical Package for the Social Sciences software (SPSS), including Spearman's rho correlation coefficient, Friedman's two-way Analysis Of Variance (ANOVA) for comparison of distributions; bias was compared by way of mean and standard deviation.Results:The CellaVision reticulocyte counts correlated most strongly with those of the analyzer (often considered the benchmark test); the reticulocyte count distributions were noted not to be significantly different from each other across all three methods. The mean and standard deviation of bias were lowest in the comparison of CellaVision and LH750 counts.Conclusions:Our data provide additional support for the accuracy of digital hematology applications using the CellaVision DM96 platform.