Leukocyte differential based on an imaging and impedance flow cytometry of microfluidics coupled with deep neural networks

The differential of leukocytes functions as the first indicator in clinical examinations. However, microscopic examinations suffered from key limitations of low throughputs in classifying leukocytes while commercially available hematology analyzers failed to provide quantitative accuracies in leukocyte differentials. A home-developed imaging and impedance flow cytometry of microfluidics was used to capture fluorescent images and impedance variations of single cells traveling through constrictional microchannels. Convolutional and recurrent neural networks were adopted for data processing and feature extractions, which were then fused by a support vector machine to realize the four-part differential of leukocytes. The classification accuracies of the four-part leukocyte differential were quantified as 95.4% based on fluorescent images plus the convolutional neural network, 90.3% based on impedance variations plus the recurrent neural network, and 99.3% on the basis of fluorescent images, impedance variations, and deep neural networks. Based on single-cell fluorescent imaging and impedance variations coupled with deep neural networks, the four-part leukocyte differential can be realized with almost 100% accuracy.

Electrical micro flow cytometry with LSTM and its application in leukocyte differential

This paper developed an electrical micro flow cytometry to realize leukocyte differentials leveraging a constrictional microchannel and a deep neural network. Firstly, purified granulocytes, lymphocytes or monocytes traveled through the constrictional microchannel with a cross-sectional area marginally larger than individual cells and produced large impedance variations by blocking focused electric field lines. By optimizing key elements (e.g., normalization, learning rate, batch size and neuron number) of the recurrent neural network (RNN), electrical results of purified leukocytes were analyzed to establish a leukocyte differential system with a classification accuracy of 95.2%. Then the leukocyte mixtures were forced to travel through the same constrictional microchannel, producing mixed impedance profiles which were classified into granulocytes, lymphocytes and monocytes based on the aforementioned differential system. As to the classification results, two leukocyte mixtures from the same donor were processed, producing comparable classification results, which were 57% versus 59% of granulocytes, 37% versus 34% of lymphocytes and 6% versus 7% of monocytes. These results validated the established classification system based on the constrictional microchannel and the recurrent neural network, providing a new perspective of differentiating white blood cells by electrical flow cytometry.

Evaluation of the New Beckmann Coulter Analyzer DxH 900 Compared to Sysmex XN20: Analytical Performance and Flagging Efficiency

Efficiency and accuracy in automated hematology analyzers are very important for clinical laboratories. The purpose was to evaluate the flags and results reported by the newest Beckman Coulter analyzer DxH 900 compared to the Sysmex XN20 system. Samples were analyzed on the XN20 (Sysmex, Kobe, Japan) and on the Beckman Coulter DxH 900 (Beckman Coulter, Miami, Florida, USA). Slide reviews were performed microscopically. Morphologic criteria were used to identify abnormal cells as recommended by International Consensus Group for Hematology (ICSH): blasts, immature granulocytes (IG%), abnormal lymphocytes (ALs) and plasma cells. Results: there was a strong correlation between the analyzers in almost all clinical parameters tested. Both DxH 900 and XN20 showed an excellent degree of association for the leukocyte differential compared to the reference method (manual microscopy). When it comes to IG%, XN20 showed a positive bias for higher results. Related to platelets, there are no differences between the two methods for PLT count. For mean platelet volume (MPV), DxH 900 provided 100% results of the samples analyzed while XN20 while in the XN20 analyzer, 16% of the results were missing. From our results we came to the conclusion that both analyzers, DxH 900 and XN20 were clinically accurate and efficient. Abnormal Lymphocyte detection highlighted the differences between the two technologies as only minimal agreement was obtained. DxH 900 demonstrated higher sensitivity in detecting IG with good correlation with microscopic review. The DxH 900 for platelet clumps identification provides an excellent flag (PLT Clumps) with the highest sensitivity observed in our evaluation.

Performance evaluation of the new hematology analyzer UniCel DxH 900

INTRODUCTION

UniCel DxH900 (Beckman Coulter, Miami, Florida, USA) is a quantitative, multi-parameter, automated hematology analyzer for in vitro diagnostic use in clinical laboratories. The aim of this study was to evaluate the analytical performance of the new DxH900 analyzer to verify its diagnostic and clinical utility in the hematology laboratory of a tertiary care hospital in Spain. The most important and novel feature offered by DxH900 analyzer is providing MDW (monocyte distribution width), a new hematologic parameter which is being clinically validated as an early sepsis indicator with promising results.

METHODS

We evaluated imprecision (including MDW), linearity, and carryover of DxH900. Method comparison for cell blood count (CBC) was performed in relation to DxH800 with 100 samples. We compared leukocyte differential (DIFF) from DxH900 with manual 400-cell differential. 390 samples were assessed for flag performance.

RESULTS

Results obtained for between days and within-run imprecision were good. DxH900 showed excellent linearity (R = 1.00) over analytical range for white blood cells, red blood cells, hemoglobin, platelets, and reticulocyte count (RET) (R = 0.96) and no significant carryover effect. CBC and RET on the DxH900 correlated well with DxH800 (R ≥ 0.99). Comparison with manual differential showed excellent correlation (R ≥ 0.88), except for basophils. Flagging performance exhibited sensitivity over 90% for majority of alarm messages and very high negative predictive value (over 95%).

CONCLUSION

UniCel DxH900 Coulter analyzer provides reliable results and fully comparable to DxH800. DxH900 is an accurate, highly precise analyzer with good analytical performances to be used effectively in high-volume laboratories.

Development of Blood-Cell-Selective Fluorescent Biodots for Lysis-Free Leukocyte Imaging and Differential Counting in Whole Blood

Complete blood count with leukocyte (white blood cell, WBC) differential is one of the most frequently ordered clinical test for disease diagnosis. Herein, multifunctional fluorescent carbon dots derived from biomolecules (biodots) for rapid lysis-free whole blood analysis are developed. Specifically, two types of biodots are molecularly engineered through hydrothermal synthesis for differential blood cells labeling. Type I biodots synthesized from amino acid (serine/threonine) precursors and passivated with polyethylenimine can label both red blood cells (RBCs) and WBCs with excellent contrast in fluorescence intensity, enabling direct counting of leukocytes in whole blood samples without a tedious RBC lysis step. It also allows three-part leukocyte differential counting by flow cytometry without using expensive fluorophore-conjugated antibodies. On the other hand, Type II biodots synthesized from the same amino acid precursors but passivated with a biopolymer (chitosan) are able to selectively lyse RBCs with greater than 98% efficiency to allow simultaneous fluorescent labeling of leukocytes for WBC counting in whole blood. It is envisioned that these novel nanoreagents, which eliminate the cumbersome lysis and antibody conjugation steps for selective labeling of different blood cells, would revolutionize disease diagnostics toward achieving faster, cheaper, and more accurate whole blood analyses in one test.

Hematology reference intervals for adult cows in France using the Sysmex XT-2000iV analyzer

In order to develop bovine hematology reference intervals (RIs) in accordance with new international recommendations, we analyzed 156 blood specimens of healthy adult dairy and beef cows from 32 farms with a Sysmex XT-2000iV analyzer, and by manual scoring of platelet clumps and white blood cell (WBC) differential. We established RIs by the nonparametric method, and examined effects of age, production type (beef vs. dairy), and stage of lactation. RIs could not be determined for platelet count and indices because clumps were observed in 80% of specimens. Optical and impedance red blood cell (RBC) counts were similar, although statistically different. RIs for analyzer and manual WBC differentials were not different except for lymphocyte concentration, the subpopulations of which were counted manually. Hematocrit was higher in beef than dairy cattle, and hemoglobin was lower in early lactation. Increases in RBC count, mean corpuscular volume, mean corpuscular hemoglobin, and RBC distribution width were noted with increasing age, along with decreases in WBC count, neutrophils, and lymphocytes. Most RIs in our study, with the exception of neutrophils, were similar to those previously reported using a flow cytometry analyzer.

Flow cytometric white blood differential using CytoDiff™ in the diagnosis of neonatal early-onset infection

OBJECTIVE

Neonatal early-onset infection is a life-threatening disease, requiring early diagnosis and treatment. Newborns at risk are identified by a combination of risk factors, clinical signs of infection and laboratory parameters such as white blood cell count and C-reactive protein (CRP). This method is labor-intensive, time consuming and has a variable reproducibility. New reliable diagnostic markers are needed to identify neonatal infection. This study presents additional leukocyte differential parameters produced by the automated flow cytometry and processing software using CytoDiff™ reagent (Beckman Coulter) in newborns suspected for early-onset infection.

METHODS

An analytic prospective observational case-control study was performed in which 185 newborns were included and retrospectively allocated into two groups, "infection likely" and "infection unlikely". Leukocyte parameters of the CytoDiff™ technique were compared with microscopic slide differentiation and routine tests.

RESULTS

We showed significant lower numbers of monocytes, CD16(-) monocytes and lymphocytes (including T+/NK-lymphocytes) in neonates suspected for early-onset infection using CytoDiff™ technique. The manual counting did not demonstrate changes with respect to the number of monocytes in these neonates.

CONCLUSIONS

The automated routine CytoDiff™ leukocyte differential provides an interesting additional diagnostic tool, next to routine laboratory diagnostics, in the diagnosis of neonatal early-onset infection.

One tube with eight antibodies for 14-part bone marrow leukocyte differential using flow cytometry

BACKGROUND

Bone marrow analysis by flow cytometry is part of the routine diagnosis of hematological disorders in medical laboratories. Differential leukocyte count and identification of abnormal cell subsets is currently performed through morphological examination on bone marrow smears by skilled cytologists. In this work, we propose a single 8-color tube for providing equivalent information, using flow cytometry.

METHODS

99 bone marrow samples were classified into 2 groups, (i) 51 samples, obtained from either healthy donors (n = 4) or patients with various diseases at diagnosis or during remission that did not present a hematological malignancy (n = 47), and (ii) 48 pathological samples with quantitative and/or qualitative abnormalities. A panel of eight antibodies-CD3-FITC/CD10-PE/CD38-PerCP-Cy5.5/CD19-PECy7/CD36-APC/CD16-APC-H7/CD34-BV421/CD45-V500-was tested to identify the main cell subsets at different stages of maturation using a FACSCanto-II analyzer.

RESULTS

We first proposed a strategy of sequential gating leading to the identification of 14 leukocyte subsets, that is, erythroblasts, monocytes, B-lymphoid cells from hematogones to plasma-cells (5 subsets), T- and NK-cells, polymorphonuclear cells (neutrophils, eosinophils, and basophils), myeloblasts and other immature granular cells. This approach was validated by comparing flow cytometry and microscopic morphological examination, both in cases of normal and abnormal samples. Interestingly, cell identification, and numeration by flow cytometry was easy to perform and highly reproducible.

CONCLUSION

A very simple, rapid, and reproducible flow cytometric approach, using a combination of eight antibodies allows determination of the cellular composition of bone marrow with high precision. © 2016 International Clinical Cytometry Society.