Performance Evaluation of the CellaVision DM96 System

Kratz, Alexander; Bengtsson, Hans-Inge; Casey, Jeanne E.; Keefe, Joan M.; Beatrice, Gail H.; Grzybek, Debera Y.; Lewandrowski, Kent; Cott, Elizabeth M. Van

doi:10.1309/xmb9-k0j4-1lhl-atay

Cited by 32 publications

(45 citation statements)

References 10 publications

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“…Another study showed that when direct microscopy was used as the reference method against, which the results of the CellaVision ® DM96 were compared, with all discrepant results included in the analysis, the specificity was 82–93% and sensitivity was 25–91%, – which was similar to the results of this study. [4] Finally, another study reported that blood cell and platelet morphology was judged to be adequate; however it was not specific for RBC morphological abnormalities. [11]…”

Section: Discussionmentioning

confidence: 99%

“…[1] Recent advances in laboratory medicine have allowed for automated devices, like the CellaVision ® DM96 (CCS; CellaVision, Lund, Sweden), to screen for specific cell abnormalities at a much more efficient rate than without automation. [234567] Previous evaluations of these types of systems have shown good correlations with the manual differentiation of normal cells. [489]…”

Section: Introductionmentioning

confidence: 99%

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Performance of the CellaVision® DM96 system for detecting red blood cell morphologic abnormalities

Horn

Mansoor

Wood

et al. 2015

Journal of Pathology Informatics

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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.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Performance of the CellaVision® DM96 system for detecting red blood cell morphologic abnormalities

Horn

Mansoor

Wood

et al. 2015

Journal of Pathology Informatics

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“…Published studies have reported a median leukocyte differential count accuracy of 90.3% in comparison to reference manual differentials. [456714] Others have reported a range of accuracy of pre-classification of erythrocyte morphological abnormalities from 65% to 98%, depending on the nature of the abnormality. [16] Still others have evaluated platelet-counting concordance relative to standards, noting a range of correlation coefficients from 0.92 to 0.94.…”

Section: Discussionmentioning

confidence: 99%

“…[1] The CellaVision platforms are among the most thoroughly studied digital hematology platforms in use. Indeed, a review of the literature highlights the rigorous evaluation that the CellaVision system has undergone by multiple groups and from multiple perspectives: Several studies have supported the accuracy and precision of CellaVision for the purposes of the leukocyte differential;[23456789101112131415] others have highlighted the accuracy and precision of CellaVision in the analysis of red cell parameters;[345111316] others still have validated CellaVision for use in platelet counting and morphological assessment. [3111317] In reviewing the literature, only a single publication could be identified pertaining to the evaluation of digitized slide analysis for the purpose of reticulocyte counting;[18] however, no CellaVision-specific data was identified.…”

Section: Introductionmentioning

confidence: 99%

Accuracy of the CellaVision DM96 platform for reticulocyte counting

Mahé

Higa

Naugler

et al. 2014

Journal of Pathology Informatics

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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.

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“…It comprises: an automated microscope that scans the blood smear; a digital camera that captures images of all the cellular and particulate material on the slide; and a computer that classifies each image by means of complex algorithms. It has been demonstrated to have good performance characteristics in developed countries, 5,6,7,8,9 but to date has not been evaluated in Africa, where the spectrum of pathology encountered is very different. Most notable in sub-Saharan Africa is the extremely high prevalence of HIV infection.…”

Section: Introductionmentioning

confidence: 99%

Evaluation of the accuracy of the CellaVision™ DM96 in a high HIV-prevalence population in South Africa

2016

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IntroductionThe CellaVision™ DM96 (DM96) is a digital microscopy system which performs well in developed countries. However, to date it has not been evaluated in Africa, where the pathology spectrum encountered is very different. In particular, its utility in a setting with high HIV prevalence has not been assessed, which is of interest because of the morphological aberrations often seen in HIV-positive patients.ObjectivesThis study aimed to evaluate the accuracy of the DM96 in a South African laboratory, with emphasis on its performance in samples collected from HIV-positive patients.MethodsA total of 149 samples submitted for a routine differential white cell count in 2012 and 2013 at the Chris Hani Baragwanath Academic Hospital in Johannesburg, South Africa were included, of which 79 (53.0%) were collected from HIV-positive patients. Results of DM96 analysis pre- and post-classification were compared with a manual differential white cell count and the impact of HIV infection and other variables of interest were assessed.ResultsPre- and post-classification accuracies were similar to those reported in developed countries. Reclassification was required in 16% of cells, with particularly high misclassification rates for eosinophils (31.7%), blasts (33.7%) and basophils (93.5%). Multivariate analysis revealed a significant relationship between the number of misclassified cells and both the white cell count (p = 0.035) and the presence of malignant cells in the blood (p = 0.049), but not with any other variables analysed, including HIV status.ConclusionThe DM96 exhibited acceptable accuracy in this South African laboratory, which was not impacted by HIV infection. However, as it does not eliminate the need for experienced morphologists, its cost may be unjustifiable in a resource-constrained setting.

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Performance Evaluation of the CellaVision DM96 System

Cited by 32 publications

References 10 publications

Performance of the CellaVision® DM96 system for detecting red blood cell morphologic abnormalities

Performance of the CellaVision® DM96 system for detecting red blood cell morphologic abnormalities

Accuracy of the CellaVision DM96 platform for reticulocyte counting

Evaluation of the accuracy of the CellaVision™ DM96 in a high HIV-prevalence population in South Africa

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