Literature DB >> 29317138

Evaluation of the CellaVision DM96 advanced RBC application for screening and follow-up of malaria infection.

Lisa Florin1, Karel Maelegheer1, Astrid Muyldermans1, Marjan Van Esbroeck2, Eric Nulens3, Jan Emmerechts4.   

Abstract

CellaVision DM96 is a digital cell morphology system for automated classification of white and red blood cells. CellaVision Advanced RBC application (ARBCA) pre-classifies RBC in 21 categories, including parasitized RBC, and allows re-classification by the operator. In this study, the performance of the software for detection of malaria and calculation of parasitemia was evaluated and compared to microscopy (n=40). For CellaVision, both pre- and post-reclassification results were evaluated. Sensitivity was moderate, even post-reclassification (72%), due to low numbers of analyzed RBC and limited resolution of photographs. CellaVision results correlated with microscopy according to Passing-Bablok analysis, with slightly lower values for CellaVision. Within-run, between-run and inter-observer variability were acceptable. The low sensitivity of CellaVision ARBCA precludes its use as a screening technique for malaria. However, due to its good correlation with microscopy and short turn-around-times, it may be useful in follow-up of parasitemia. Larger studies are required to confirm these findings.
Copyright © 2017 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  CellaVision; Diagnosis; Malaria; Parasitemia

Mesh:

Year:  2017        PMID: 29317138     DOI: 10.1016/j.diagmicrobio.2017.12.002

Source DB:  PubMed          Journal:  Diagn Microbiol Infect Dis        ISSN: 0732-8893            Impact factor:   2.803


  2 in total

1.  Computer Vision and Artificial Intelligence Are Emerging Diagnostic Tools for the Clinical Microbiologist.

Authors:  Daniel D Rhoads
Journal:  J Clin Microbiol       Date:  2020-05-26       Impact factor: 5.948

Review 2.  Mini Review: Clinical Routine Microbiology in the Era of Automation and Digital Health.

Authors:  Stefano Leo; Abdessalam Cherkaoui; Gesuele Renzi; Jacques Schrenzel
Journal:  Front Cell Infect Microbiol       Date:  2020-11-30       Impact factor: 5.293

  2 in total

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