How Reproducible Is the Data from Sysmex DI-60 in Leukopenic Samples?

Performance evaluation of the digital morphology analyser Sysmex DI-60 for white blood cell differentials in abnormal samples

Sysmex DI-60 enumerates and classifies leukocytes. Limited research has evaluated the performance of Sysmex DI-60 in abnormal samples, and most focused on leukopenic samples. We evaluate the efficacy of DI-60 in determining white blood cell (WBC) differentials in normal and abnormal samples in different WBC count. Peripheral blood smears (n = 166) were categorised into normal control and disease groups, and further divided into moderate and severe leucocytosis, mild leucocytosis, normal, mild leukopenia, and moderate and severe leukopenia groups based on WBC count. DI-60 preclassification and verification and manual counting results were assessed using Bland-Altman and Passing-Bablok regression analyses. The Kappa test compared the concordance in the abnormal cell detection between DI-60 and manual counting. DI-60 exhibited notable overall sensitivity and specificity for all cells, except basophils. The correlation between the DI-60 preclassification and manual counting was high for segmented neutrophils, band neutrophils, lymphocytes, and blasts, and improved for all cell classes after verification. The mean difference between DI-60 and manual counting for all cell classes was significantly high in moderate and severe leucocytosis (WBC > 30.0 × 109/L) and moderate and severe leukopenia (WBC < 1.5 × 109/L) groups. For blast cells, immature granulocytes, and atypical lymphocytes, the DI-60 verification results were similar to the manual counting results. Plasma cells showed poor agreement. In conclusion, DI-60 demonstrates consistent and reliable analysis of WBC differentials within the range of 1.5-30.0 × 109. Manual counting was indispensable in examining moderate and severe leucocytosis samples, moderate and severe leukopenia samples, and in enumerating of monocytes and plasma cells.

Evaluation of the Sysmex DI-60 digital morphology analyzer on Wright-stained samples with a focus on prevalence-dependent quality indicators

BACKGROUND

This study aims to evaluate the trueness of the DI-60 Digital Cell Imaging Analyzer on Wright-stained samples with a focus on prevalence-dependent quality indicators for differential blood counts requested from non-hematology wards.

METHODS

Two hundred and ninety-nine samples were included into this performance evaluation study at the Department of Laboratory Medicine, Medical University of Vienna. The following aspects were verified: (a) the reliability of automatedly pre-classified differential counts, (b) the concordance of DI-60 counts with manual-microscopic differential counts and (c) the agreement of DI-60 and manual-microscopic results regarding clinically relevant findings.

RESULTS

82.3% of all leukocytes were correctly pre-classified. Cell categories with a low prevalence (eosinophils, basophils, progenitors/precursors) in non-hematological patients presented with a low positive predictive value (PPV), indicating a high frequency of false positives. Comparisons between visually adjusted results of the DI-60 and manual-microscopic differential counts revealed a good concordance for neutrophil and lymphocyte counts. Besides the detection of precursors/progenitors and normoblasts, no relevant systemic errors were detected. However, due to their low prevalence and technical aspects, the detection of basophilia, monocytosis or the presence of precursors/progenitors showed comparably low accuracies (error rates of 7.4%-24.1%).

CONCLUSION

The DI-60 system works well for Wright-stained samples collected in the non-hematology ward. Due to the varying prevalence of cell categories found in peripheral blood, a low PPV can be expected with automatic assignment for those cells with low prevalence (e.g., basophils, eosinophils, precursor and progenitor cells, plasma cells). If the pre-test probability of these conditions is increased, manual microscopic processing may be recommended.

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

INTRODUCTION

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.

METHODS

The cell identification performance of Mindray MC-80 was evaluated for sensitivity and specificity using pre-classification 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

The precision was within the acceptable limit for all cell classes. Overall, the specificity of cell identification was higher than 95% for all cell classes. The sensitivity was greater for 95% for most cell classes, except for myelocytes (94.9%), metamyelocytes (90.9%), reactive lymphocytes (89.7%), and plasma cells (60%). Pre-classification and post-classification 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 promyelocytes, metamyelocytes, basophils, and reactive lymphocytes.

CONCLUSION

The performance of Mindray MC-80 for white blood cell differentials is reliable and seems to be acceptable even in abnormal samples. However, the sensitivity is less than 95% for certain abnormal cell types, so the user should be aware of this limitation where such cells are suspected.

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

INTRODUCTION

Digital morphology analyzers are increasingly replacing light microscopy in laboratory hematology practice. This study aimed to perform the analytical validation of the white blood cell (WBC) differential and of reliability of platelet assessment on Sysmex DI-60 (Kobe, Japan).

METHODS

Validation included determination of within-run and between-run precision for WBC differential according to the CLSI EP15-A3 protocol, accuracy and method comparison with light microscopy and with the automated WBC differential from the Sysmex XN-10 hematology analyzer, reliability of platelet clump detection and platelet count estimation.

RESULTS

Standard deviations of both pre- and post-classification mostly satisfied manufacturer's criteria for imprecision. Accuracy assessment revealed that only eosinophil count (1.4%) in one peripheral blood smear (PBS) remained outside the declared range (2-10%) after reclassification. Method comparison between DI-60 and light microscopy yielded Spearman's correlation coefficients from 0.37 (basophils) to 0.94 (neutrophils and lymphocytes), minor proportional difference for bands, constant difference for monocytes, both constant and proportional difference for lymphocytes and statistically significant biases for bands, lymphocytes, monocytes and basophils. Diagnostic sensitivity (Se) and specificity (Sp) of DI-60 in detecting immature/pathological cells were 88.7% (95%CI:81.1-94.0) and 83.0% (95%CI:78.7-86.7), respectively, with the area under the curve (AUC) of 0.86 (95%CI:0.82-0.89). Agreement in detection of platelet clumps was 94.8% (kappa coefficient = 0.67, 95%CI:0.53-0.80). Se and Sp of DI-60 to detect platelet clumps were 65.7% (95%CI: 47.8-80.9) and 96.9% (95%CI: 93.9-98.6), respectively, while AUC was 0.81 (95%CI: 0.76-0.86).

CONCLUSION

DI-60 provides reliable WBC differential and platelet assessment. In doubtful cases, the use of light microscopy is still mandatory.

Performance of digital morphology analyzer Medica EasyCell assistant

OBJECTIVES

The EasyCell assistant (Medica, Bedford, MA, USA) is one of the state-of-the-art digital morphology analyzers. We explored the performance of EasyCell assistant in comparison with manual microscopic review and Pentra DX Nexus (Horiba ABX Diagnostics, Montpellier, France).

METHODS

In a total of 225 samples (100 normal and 125 abnormal samples), white blood cell (WBC) differentials and platelet (PLT) count estimation by EasyCell assistant were compared with the results by manual microscopic review and Pentra DX Nexus. The manual microscopic review was performed according to the Clinical and Laboratory Standards Institute guidelines (H20-A2).

RESULTS

WBC differentials between pre-classification by EasyCell assistant and manual counting showed moderate correlations for neutrophils (r=0.58), lymphocytes (r=0.69), and eosinophils (r=0.51) in all samples. After user verification, they showed mostly high to very high correlations for neutrophils (r=0.74), lymphocytes (r=0.78), eosinophils (r=0.88), and other cells (r=0.91). PLT count by EasyCell assistant highly correlated with that by Pentra DX Nexus (r=0.82).

CONCLUSIONS

The performance of EasyCell assistant for WBC differentials and PLT count seems to be acceptable even in abnormal samples with improvement after user verification. The EasyCell assistant, with its reliable performance on WBC differentials and PLT count, would help optimize the workflow of hematology laboratories with reduced workload of manual microscopic review.

Analytical performance of the digital morphology analyzer Sysmex DI-60 for body fluid cell differential counts

BACKGROUND

Sysmex DI-60 (Sysmex, Kobe, Japan) is a digital morphology (DM) analyzer widely used in clinical laboratories and supports body fluid (BF) applications. We evaluated analytical performance of DI-60 compared with XN-350 (Sysmex) and manual counting for BF cell differential counts.

METHODS

A total of 213 BF samples were collected (47 cerebrospinal fluid [CSF], 80 pleural fluid, and 86 ascites samples). The analytical performance of DI-60 for BF cell differential counts was evaluated based on sensitivity, specificity, accuracy, and agreement. BF cell differential counts obtained by DI-60 were compared with those obtained by XN-350 and manual counting.

RESULTS

The overall sensitivity was high for neutrophils, lymphocytes, and macrophages (range, 83.1-99.4%). The overall specificity and overall accuracy were high for all cell types (range, 95.3-99.7% and 94.3-99.3%, respectively). The agreement between DI-60 pre-classification and verification was strong (κ = 0.89). The absolute mean differences between DI-60 verification and XN-350 ranged from 0.26 to 11.05, and differences between DI-60 verification and manual counting ranged from 0.01 to 4.76.

CONCLUSIONS

This is the first study to evaluate the performance of DI-60 compared with XN-350 and manual counting for BF cell differential counts. DI-60 showed reliable performance with CSF, pleural fluid, and ascites samples. For BF cell differential counts, DI-60 may be a better option than XN-350 and could be used for screening purposes in understaffed laboratories. To improve the hematology workflow for BF cell differential counting, the DM analyzer needs to be optimized by taking into account the laboratory situation and unmet needs, and the clinical laboratory needs to establish criteria for verification and manual slide review.

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

White blood cell differentials performance of a new automated digital cell morphology analyzer: Mindray MC-80, K. Paisooksantivatana; N. Khongjaroensakun; P. Chinudomwong; N. Chaothai; L. Chamchomdao; K. Suriyachand, International Journal of Laboratory Hematology, 10.1111/ijlh.13995 The above article, published online on 18 November 2022, in Wiley Online Library (wileyonlinelibrary.com), had been retracted by agreement between the authors, the journal's Editors-in-Chief, Giuseppe D'Onofrio and Ian Mackie, and John Wiley & Sons. The authors contacted the journal after publication to propose extensive changes to the data presented in the accepted article such that it would no longer reflect the version that was peer reviewed. As a result, this retraction has been undertaken.

Performance of digital morphology analyzer CellaVision DC-1

OBJECTIVES

CellaVision DC-1 (DC-1, Sysmex, Kobe, Japan) is a newly launched digital morphology analyzer that was developed mainly for small to medium-volume laboratories. We evaluated the precision, qualitative performance, comparison of cell counts between DC-1 and manual counting, and turnaround time (TAT) of DC-1.

METHODS

Using five peripheral blood smear (PBS) slides spanning normal white blood cell (WBC) range, precision and qualitative performance of DC-1 were evaluated according to the Clinical and Laboratory Standards Institute (CLSI) EP15-A3, EP15-Ed3-IG1, and EP12-A2 guidelines. Cell counts of DC-1 and manual counting were compared according to the CLSI EP 09C-ED3 guidelines, and TAT of DC-1 was also compared with TAT of manual counting.

RESULTS

DC-1 showed excellent precision (%CV, 0.0-3.5%), high specificity (98.9-100.0%), and high negative predictive value (98.4-100.0%) in 18 cell classes (12 WBC classes and six non-WBC classes). However, DC-1 showed 0% of positive predictive value in seven cell classes (metamyelocytes, myelocytes, promyelocytes, blasts, plasma cells, nucleated red blood cells, and unidentified). The largest absolute mean differences (%) of DC-1 vs. manual counting was 2.74. Total TAT (min:s) was comparable between DC-1 (8:55) and manual counting (8:55).

CONCLUSIONS

This is the first study that comprehensively evaluated the performance of DC-1 including its TAT. DC-1 has a reliable performance that can be used in small to medium-volume laboratories for assisting PBS review. However, DC-1 may make unnecessary workload for cell verification in some cell classes.

Multicentric evaluation of the variability of digital morphology performances also respect to the reference methods by optical microscopy

INTRODUCTION

Despite the important diagnostic role of peripheral blood morphology, cell classification is subjective. Automated image-processing systems (AIS) provide more accurate and objective morphological evaluation. The aims of this multicenter study were the evaluation of the intra and inter-laboratory variation between different AIS in cell pre-classification and after reclassification, compared with manual optical microscopy, the reference method.

METHODS

Six peripheral blood samples were included in this study, for each sample, 70 May-Grunwald and Giemsa stained PB smears were prepared from each specimen and 10 slides were delivered to the seven laboratories involved. Smears were processed by both optical microscopy (OM) and AIS. In addition, the assessment times of both methods were recorded.

RESULTS

Within-laboratory Reproducibility ranged between 4.76% and 153.78%; between-laboratory Precision ranged between 2.10% and 82.2%, while Total Imprecision ranged between 5.21% and 20.60%. The relative Bland Altman bias ranged between -0.01% and 20.60%. The mean of assessment times were 326 ± 110 s and 191 ± 68 s for AIS post reclassification and OM, respectively.

CONCLUSIONS

AIS can be helpful when the number of cell counted are low and can give advantages in terms of efficiency, objectivity and time saving in the morphological analysis of blood cells. They can also help in the interpretation of some morphological features and can serve as learning and investigation tools.

Digital Morphology Analyzer Sysmex DI-60 vs. Manual Counting for White Blood Cell Differentials in Leukopenic Samples: A Comparative Assessment of Risk and Turnaround Time

Background

Digital morphology (DM) analyzers are increasingly being used for white blood cell (WBC) differentials. We assessed the laboratory efficiency of the Sysmex DI-60 system (DI-60; Sysmex, Kobe, Japan) in comparison with manual counting in leukopenic samples.

Methods

In total, 40 peripheral blood smear samples were divided into normal, mild leukopenia, moderate leukopenia, and severe leukopenia groups based on WBC count. In each group, the risk and turnaround time (TAT) were compared between DI-60 and manual counting. Risk was determined by failure mode and effect analysis using the risk priority number (RPN) score, and TAT was recorded for the analytical phase.

Results

Overall, DI-60 showed a five-fold lower risk (70 vs. 350 RPN) and longer TAT than manual counting. In severe leukopenic samples, DI-60 showed a shorter TAT/slide and a remarkably lower cell count/slide than manual counting. In all samples, the TAT/cell for DI-60 was substantially longer than that for manual counting (DI-60 vs. manual total, 1.8 vs. 1.0 sec; normal, 1.5 vs. 0.7 sec; mild leukopenia, 1.9 vs. 0.9 sec; moderate leukopenia, 1.8 vs. 1.0 sec; severe leukopenia, 28.8 vs. 19.0 sec).

Conclusions

This is the first comparative assessment of risk and TAT between DI-60 and manual counting in leukopenic samples. DI-60 decreases the laboratory risk and improves patient safety, but requires more time to count fewer cells, especially in severe leukopenic samples. DM analyzers should be applied selectively depending on the WBC count to optimize laboratory efficiency.