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.

BACKGROUND: Few studies have evaluated digital morphology (DM) analyzers on body fluids (BF). We evaluated the performance of a DM analyzer, Sysmex DI-60 (Sysmex, Kobe, Japan) for white blood cell (WBC) differentials in BF samples.
METHODS: In five BF samples (two pleural fluids and three ascites) containing a single, dominant cell type (>80%, neutrophils, lymphocytes, macrophages, abnormal lymphocytes, and malignant cells in each sample), we evaluated the precision of the DI-60 and compared the WBC differentials and turnaround times (TAT) between DI-60 and manual counting.
RESULTS: The precision of the DI-60 pre-classification and verification was excellent (%CV, 0.01-3.16%). After verification, the DI-60 showed high sensitivity, specificity, and efficiency (ranges: 90.8-98.1%, 96.8-97.9%, and 92.5-98.0%, respectively) for the dominant cell types in neutrophil- and lymphocyte-dominant samples. For all samples, the DI-60 and manual counting showed high correlations for major cell types (neutrophils, lymphocytes, macrophages, and others, r = 0.72 to 0.94) after verification. The agreement between the pre-classification and verification of the DI-60 was strong in the neutrophil-dominant sample (κ = 0.81). The DI-60 showed a significantly longer TAT (min: s) than manual counting for all samples (median TAT/slide: 6:28 vs. 1:53, p < 0.0001), with remarkable differences in abnormal lymphocyte- and malignant cell-dominant samples (21:05 vs. 2:06; 12:34 vs. 2:25).
CONCLUSIONS: The DI-60 may provide reliable data in neutrophil- and lymphocyte-dominant BF samples. However, it may require longer times and higher workloads for WBC differentials especially in BF samples containing atypical cells. Further improvement would be needed before applying DM analyzers for routine clinical practice in BF analysis.

BACKGROUND: Digital pathology artificial intelligence (AI) platforms have the capacity to improve over time through \"deep machine learning.\" We have previously reported on the accuracy of peripheral white blood cell (WBC) differential and blast identification by Techcyte (Techcyte, Inc., Orem, UT, USA), a digital scanner-agnostic web-based system for blood film reporting. The aim of the current study was to compare AI protocols released over time to assess improvement in cell identification.
METHODS: WBC differentials were performed using Techcyte\'s online AI software on the same 124 digitized abnormal peripheral blood films (including 64 acute and 22 chronic leukaemias) in 2019 (AI1), 2020 (AI2), and 2022 (AI3), with no reassignment by a morphologist at any time point. AI results were correlated to the \"gold standard\" of manual microscopy, and comparison of Lin\'s concordance coefficients (LCC) and sensitivity and specificity of blast identification were used to determine the superior AI version.
RESULTS: AI correlations (r) with manual microscopy for individual cell types ranged from 0.50-0.90 (AI1), 0.66-0.86 (AI2) and 0.71-0.91 (AI3). AI3 concordance with manual microscopy was significantly improved compared to AI1 for identification of neutrophils (LCC AI3 = 0.86 vs. AI1 = 0.77, p = 0.03), total granulocytes (LCC AI3 = 0.92 vs. AI1 = 0.82, p = 0.0008), immature granulocytes (LCC AI3 = 0.67 vs. AI1 = 0.38, p = 0.0014), and promyelocytes (LCC AI3 = 0.53 vs. AI1 = 0.16, p = 0.0008). Sensitivity for blast identification (n = 65 slides) improved from 97% (AI1), to 98% (AI2), to 100% (AI3), while blast specificity decreased from 24% (AI1), to 14% (AI2) to 12% (AI3).
CONCLUSIONS: Techcyte AI has shown significant improvement in cell identification over time and maintains high sensitivity for blast identification in malignant films.

Establishing direct reference intervals for pediatric patients is a costly, challenging, and time-consuming enterprise. Indirectly established reference intervals can help to ameliorate this situation. It was our objective to establish population-specific reference intervals for automated white blood cell differentials via data mining and non-parametric percentile method.
Blood counts and automated white blood cell differentials of patients aged 0 days to 18 years, performed from the 1st of January 2018 until the 30th of June 2022, were identified in our laboratory information system. Reference intervals were established in accordance with IFCC and CLSI recommendations as well as the propositions by Haeckel et al.
Initially, 47,173 blood counts on our SYSMEX XN-9000 were identified. 11,707 data sets were excluded, leaving 35,466 sample sets for analysis. Of these, 17,616 contained automated white blood cell differentials. Due to insufficient patient numbers, no reference intervals for automated white blood cell differentials could be established for children aged <7 months. In comparison to the corresponding reference intervals published by Herklotz et al., reference intervals determined by us showed relevant differences throughout all age groups.
The combination of non-parametric percentile method and the propositions by Haeckel et al. utilizing conscientious data mining appears to be potent alternative to direct reference interval determination.

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Leukocyte differentials are a useful tool for assessing systemic immunological changes during pathogen infections, particularly for non-model species. To date, no study has explored how experimental infection with a common bacterial pathogen, Mycoplasma gallisepticum (MG), influences the course and strength of haematological changes in the natural songbird host, house finches. Here we experimentally inoculated house finches with MG isolates known to vary in virulence, and quantified the proportions of circulating leukocytes over the entirety of infection. First, we found significant temporal effects of MG infection on the proportions of most cell types, with strong increases in heterophil and monocyte proportions during infection. Marked decreases in lymphocyte proportions also occurred during infection, though these proportional changes may simply be driven by correlated increases in other leukocytes. Second, we found significant effects of isolate virulence, with the strongest changes in cell proportions occurring in birds inoculated with the higher virulence isolates, and almost no detectable changes relative to sham treatment groups in birds inoculated with the lowest virulence isolate. Finally, we found that variation in infection severity positively predicted the proportion of circulating heterophils and lymphocytes, but the strength of these correlations was dependent on isolate. Taken together, these results indicate strong haematological changes in house finches during MG infection, with markedly different responses to MG isolates of varying virulence. These results are consistent with the possibility that evolved virulence in house finch MG results in higher degrees of immune stimulation and associated immunopathology, with potential direct benefits for MG transmission. RESEARCH HIGHLIGHTS House finches show a marked pro-inflammatory response to M. gallisepticum infection. Virulent pathogen isolates produce stronger finch white blood cell responses. Among birds, stronger white blood cell responses are associated with higher infection severity.