Literature DB >> 16203273

Performance evaluation of the CellaVision DM96 system: WBC differentials by automated digital image analysis supported by an artificial neural network.

Alexander Kratz1, Hans-Inge Bengtsson, Jeanne E Casey, Joan M Keefe, Gail H Beatrice, Debera Y Grzybek, Kent B Lewandrowski, Elizabeth M Van Cott.   

Abstract

We evaluated the CellaVision DM96 (CellaVision AB, Lund, Sweden), an automated digital cell morphology and informatics system for peripheral blood smears. Technologists agreed with 82% of the instrument's preclassifications. Correlation coefficients between final results released from the CellaVision and results obtained by direct microscopy were 0.96 (all neutrophils), 0.94 (lymphocytes), 0.88 (segmented neutrophils), 0.73 (eosinophils), 0.69 (bands), and 0.67 (monocytes). After correction for statistically and clinically insignificant variations, the CellaVision DM96 had 95% sensitivity and 88% specificity for immature myeloid cells. It was 100% sensitive and 94% specific for blasts, and 100% sensitive and 97% specific for unusual WBCs and nucleated RBCs. Advantages of the CellaVision DM96 over direct microscopy include the ability to review slides from a remote location, consultation and quality control on a cell-by-cell basis, and potential labor savings.

Entities:  

Mesh:

Year:  2005        PMID: 16203273     DOI: 10.1309/XMB9-K0J4-1LHL-ATAY

Source DB:  PubMed          Journal:  Am J Clin Pathol        ISSN: 0002-9173            Impact factor:   2.493


  18 in total

1.  Examination of peripheral blood films using automated microscopy; evaluation of Diffmaster Octavia and Cellavision DM96.

Authors:  H Ceelie; R B Dinkelaar; W van Gelder
Journal:  J Clin Pathol       Date:  2006-05-12       Impact factor: 3.411

2.  Performance evaluation and relevance of the CellaVision DM96 system in routine analysis and in patients with malignant hematological diseases.

Authors:  E Cornet; J-P Perol; X Troussard
Journal:  Int J Lab Hematol       Date:  2008-12       Impact factor: 2.877

3.  Image resizing using saliency strength map and seam carving for white blood cell analysis.

Authors:  ByoungChul Ko; SeongHoon Kim; JaeYeal Nam
Journal:  Biomed Eng Online       Date:  2010-09-20       Impact factor: 2.819

4.  Experience with CellaVision DM96 for peripheral blood differentials in a large multi-center academic hospital system.

Authors:  Marian A Rollins-Raval; Jay S Raval; Lydia Contis
Journal:  J Pathol Inform       Date:  2012-08-25

5.  Platelet count estimation using the CellaVision DM96 system.

Authors:  Yuon Gao; Adnan Mansoor; Brenda Wood; Heather Nelson; Diane Higa; Christopher Naugler
Journal:  J Pathol Inform       Date:  2013-06-29

6.  Performance of CellaVision DM96 in leukocyte classification.

Authors:  Lik Hang Lee; Adnan Mansoor; Brenda Wood; Heather Nelson; Diane Higa; Christopher Naugler
Journal:  J Pathol Inform       Date:  2013-06-29

7.  Flow cytometric white blood cell differential using CytoDiff is excellent for counting blasts.

Authors:  Jimin Kahng; Yonggoo Kim; Myungshin Kim; Eun-Jee Oh; Yeon-Joon Park; Kyungja Han
Journal:  Ann Lab Med       Date:  2014-12-08       Impact factor: 3.464

8.  Validation of the Sysmex sp-1000i automated slide preparer-stainer in a clinical laboratory.

Authors:  Eberson Damião Dos Santos de Bitencourt; Carlos Franco Voegeli; Gabriela Dos Santos Onzi; Sara Cardoso Boscato; Carine Ghem; Terezinha Munhoz
Journal:  Rev Bras Hematol Hemoter       Date:  2013

9.  Accuracy of the CellaVision DM96 platform for reticulocyte counting.

Authors:  Etienne R Mahe; Diane Higa; Christopher Naugler; Adnan Mansoor; Meer-Taher Shabani-Rad
Journal:  J Pathol Inform       Date:  2014-05-26

10.  Performance of the CellaVision(®) DM96 system for detecting red blood cell morphologic abnormalities.

Authors:  Christopher L Horn; Adnan Mansoor; Brenda Wood; Heather Nelson; Diane Higa; Lik Hang Lee; Christopher Naugler
Journal:  J Pathol Inform       Date:  2015-02-24
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