Introduction: The CellaVision Advanced Red Blood Cell (RBC) Software Application is a new software for advanced morphological analysis of RBC, which automatically performs a preliminary characterization and grouping of RBC into 21 morphological categories, including schistocytes. Upon automated classification, the software offers the possibility of reclassification of RBC by the operator. The aim of this study was to evaluate the schistocyte analysis by the CellaVision Advanced RBC Application.
Methods: Schistocyte counts were evaluated comparing the automated count on a CellaVision DM96, both before and after reclassification, with the reference manual microscopic method according to the ICSH criteria. Thirty-six samples of hospitalized patients and 40 samples of controls were analyzed.
Results: Within-run, between-run and between-observer coefficients of variation were lower when counted with the CellaVision compared to the manual microscopic count. The very high sensitivity but rather poor specificity implicates the need for reclassification by the operator, following automated analysis. After reclassification, method comparison studies revealed good agreement with the manual microscopic method, with however slightly higher values of schistocytes for the automated analysis.
Conclusion: The CellaVision Advanced RBC Software Application provides a sensitive and reproducible measurement of schistocytes in peripheral blood, but still requires manual revision. Furthermore, it is an easy-to-use software and an excellent teaching tool that might contribute to standardization in the investigation of schistocyte-related conditions.
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http://dx.doi.org/10.1111/ijlh.12363 | DOI Listing |
Am J Clin Pathol
October 2024
Clinical Laboratory Science, University of Kansas Medical Center, Kansas City, KS, US.
Objectives: This quality improvement study, conducted at the Kansas City Veterans Affairs Medical Center in Kansas City, Missouri, examined the change in patient reporting after transitioning from manual to CellaVision software-guided differentials and slide reviews. The primary focus was blasts and schistocytes, given their clinical significance.
Methods: Three months of manual and CellaVision patient data were examined between May 2022 and February 2023.
Ann Biol Clin (Paris)
November 2023
Laboratory of Haematology, Université Catholique de Louvain, 10 avenue de Hippocrate, Bruxelles 1200, Belgique.
The detection of erythrocyte morphological abnormalities is a valuable and sometimes overlooked element in the diagnostic management of anemias. The aim of this article is to evaluate the clinical performance of the different detection thresholds tested by our laboratory using the Cellavision RBC Advanced module, after manual reclassification by an experienced operator, and comparing them to the guidelines by the ICSH (International Council for Standardization in Haematology). We arbitrarily set thresholds at 1% for "critical" abnormalities (tear drop cells, target cells, schizocytes and spherocytes) except for sickle cells (threshold set at 0.
View Article and Find Full Text PDFHematology
December 2023
Department of Clinical Laboratory Medicine, Xijing Hospital, Fourth Military Medical University (Air Force Medical University), Xi'an, People's Republic of China.
Objective: This study aims to evaluate the consistency of heterogeneity degree of erythrocyte volume parameters between the blood automated analyzer Sysmex-XN9000 and the advanced red blood cell software CellaVisionDI-60.
Method: 500 blood samples of volunteers were analyzed by Sysmex-XN9000 and CellaVision-DI60. The sensitivity, specificity, positive predictive value, negative predictive value, false positive rate, and false negative rate were evaluated.
Semin Diagn Pathol
March 2023
Department of Pathology and Laboratory Medicine, University of Texas, Southwestern Medical Center, Dallas, Texas, United States of America. Electronic address:
Digital pathology has a crucial role in diagnostic pathology and is increasingly a technological requirement in the field. Integration of digital slides into the pathology workflow, advanced algorithms, and computer-aided diagnostic techniques extend the frontiers of the pathologist's view beyond the microscopic slide and enable true integration of knowledge and expertise. There is clear potential for artificial intelligence (AI) breakthroughs in pathology and hematopathology.
View Article and Find Full Text PDFInt J Lab Hematol
August 2021
Department of Laboratory Medicine, Peking Union Medical College Hospital, Peking Union Medical College & Chinese Academy of Medical Sciences, Beijing, China.
Introduction: Red blood cells (RBCs) in patients with thalassemia and iron deficiency anemia (IDA) exhibit different patterns of morphological changes. However, manual quantitative analysis of the morphological changes in the RBCs is time-consuming and subjective, limiting its use in differential diagnosis. The aim of this study was to evaluate the CellaVision Advanced RBC software as a prescreening tool for differential diagnosis of thalassemia and IDA.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!