Evaluation of the Red Blood Cell Advanced Software Application on the CellaVision DM96. (20th May 2016)

• Record Type: Journal Article
• Authors: Criel, M.; Godefroid, M.; Deckers, B.; Devos, H.; Cauwelier, B.; Emmerechts, J.
• Is Part Of: International journal of laboratory hematology. Volume 38:Number 4(2016:Aug.)
• Page Start: 366
• Page End: 374
• Publication Date: 2016-05-20
• Subjects: RBC -- morphology -- automated cell analysis; Hematology -- Periodicals; Blood -- Diseases -- Periodicals; Hematology -- Periodicals; 616.15005
• DOI: 10.1111/ijlh.12497
• Languages: English
• ISSNs: 1751-5521

Abstract

Summary: Introduction: The CellaVision Advanced Red Blood Cell (RBC) Software Application is a new software for advanced morphological analysis of RBCs on a digital microscopy system. Upon automated precharacterization into 21 categories, the software offers the possibility of reclassification of RBCs by the operator. We aimed to define the optimal cut‐off to detect morphological RBC abnormalities and to evaluate the precharacterization performance of this software. Methods: Thirty‐eight blood samples of healthy donors and sixty‐eight samples of hospitalized patients were analyzed. Different methodologies to define a cut‐off between negativity and positivity were used. Sensitivity and specificity were calculated according to these different cut‐offs using the manual microscopic method as the gold standard. Imprecision was assessed by measuring analytical within‐run and between‐run variability and by measuring between‐observer variability. Results: By optimizing the cut‐off between negativity and positivity, sensitivities exceeded 80% for 'critical' RBC categories (target cells, tear drop cells, spherocytes, sickle cells, and parasites), while specificities exceeded 80% for the other RBC morphological categories. Results of within‐run, between‐run, and between‐observer variabilities were all clinically acceptable. Conclusion: The CellaVision Advanced RBC Software Application is an easy‐to‐use software that helps to detect most RBC morphological abnormalities in a sensitive and specific way without increasing work load, provided the proper cut‐offs are chosen. However, evaluation of the images by an experienced observer remains necessary.