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.
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.