Retracted: White blood cell differentials performance of a new automated digital cell morphology analyzer: Mindray MC‐80

Abstract

Background: The manual differential count has been recognized for its disadvantages, including large interobserver variability and labor-intensiveness. In this light, automated digital cell morphology analyzers have been increasingly adopted in hematology laboratories for their robustness and convenience. This study aims to evaluate the white blood cell differential performance of the Mindray MC-80, the new automated digital cell morphology analyzer. Materials and Methods:The cell identification performance of Mindray MC-80 was evaluated for sensitivity and specificity using preclassification and post-classification of each cell class. The method comparison study used manual differentials as the gold standard for calculating Pearson correlation, Passing-Bablok regression, and Bland-Altman analysis. In addition, the precision study was performed and evaluated.Results: Overall, the accuracy and specificity of cell identification were higher than 95% for all cell classes. The sensitivity was greater for 95% for most cell classes except for blast cells (86.1%), immature granulocytes (83.1%), reactive lymphocytes (79.6%), and plasma cells (25.0%). Preclassification and postclassification results correlated well with the manual differential results for all the cell types investigated. The regression coefficients were greater than 0.9 for most cell classes except for basophils and reactive lymphocytes. The precision of all normal WBC and abnormal cell classes were within the acceptable limit. Conclusion:The performance of Mindray MC-80 for WBC differentials is reliable and seems to be acceptable. However, the sensitivity is less than 90% for the certain abnormal cell types so the user should be aware of this limitation where the presence of such cells is suspected.

Performance of the new MC‐80 automated digital cell morphology analyser in detection of normal and abnormal blood cells: Comparison with the CellaVision DM9600

“…Furthermore, it is interesting to mention that the NPV for IG was 100%, which means that all images corresponding to IG were correctly pre‐classified by MC‐80. These results are similar to those published in the comparison of DLC by the MC‐80 with the manual method using a conventional microscope 16 . Additionally, our results showed good agreement between the percentages of normal WBC in pre‐ and post‐classification, quantified by high values of correlation and concordance (between 0.91 and 1).…”

“…Although numerous articles have been published on the advantages and limitations of CellaVision® technology, there are very few publications regarding the MC‐80 technology. To the best of our knowledge, Khongjaroensakun et al 16 were the first to analyse the DLC performance of the MC‐80 and make a comparison with the manual smear review, but their study included a limited number of abnormal samples. Our purpose is focused on evaluating the performance of the new MC‐80 using normal and a significant number of abnormal samples.…”

Analytical validation of white blood cell differential and platelet assessment on the Sysmex DI‐60 digital morphology analyzer

“…This is particularly pronounced in cases of leukopenic samples where a large part of the PBS needs to be scanned in order to reach 100 WBCs. Overall, the performance characteristics observed herein for WBC differential on Sysmex DI‐60 are rather uniformly seen throughout previously performed verification studies of DM analyzers, regardless of the manufacturer 6,11–15,17 . Minor heterogeneity in WBC differential performance by DM analyzers among studies pertains to the use of PBS with different quantitative and/or qualitative WBC disorders, with higher comparability observed in PBS containing only mature WBCs as well as in studies using non‐leukopenic samples.…”

“…Overall, the performance characteristics observed herein for WBC differential on Sysmex DI-60 are rather uniformly seen throughout previously performed verification studies of DM analyzers, regardless of the manufacturer. 6,[11][12][13][14][15]17 Minor heterogeneity in WBC differential performance by DM analyzers among studies pertains to the use of PBS with different quantitative and/or qualitative WBC disorders, with higher comparability observed in PBS containing only mature WBCs as well as in studies using non-leukopenic samples. Also, morphologists' skills in properly reclassifying cell images can affect the final result.…”

Enhancing thalassemia gene carrier identification in non‐anemic populations using artificial intelligence erythrocyte morphology analysis and machine learning

“…The MC‐100i is the latest fully automatic blood cell morphology analyzer that can use AI to comprehensively and rapidly analyze the morphological characteristics of leukocytes, erythrocytes, and platelets. This could increase work efficiency in blood cell morphology observing 21,22 . This study shows significant differences in erythrocyte morphology between TT and control groups.…”