Application of RhD Blood Group to Simulate Antibody Identification Test in Immunohematology Education.

BACKGROUND: Immunohematology skill education is an important part of the transfusion medicine professional training. We tried to solve the difficulty of obtaining suitable and sufficient positive samples in the immunohematology education. METHODS: Different identification panels and panel cells were created by RhD-positive red blood cells (RBCs) and RhD-negative RBCs, according to the underlying antibodies. Diluted anti-D reagent was used as simulated plasma for identification. RESULTS: The antibody identification of single antibody with dose-effect and two antibodies present at the same time were successfully simulated. CONCLUSIONS: It is a practical and cheap method for antibody identification training to use RhD blood group, especially when positive samples are short.

Nanoscale insights into hematology: super-resolved imaging on blood cell structure, function, and pathology.

Fluorescence nanoscopy, also known as super-resolution microscopy, has transcended the conventional resolution barriers and enabled visualization of biological samples at nanometric resolutions. A series of super-resolution techniques have been developed and applied to investigate the molecular distribution, organization, and interactions in blood cells, as well as the underlying mechanisms of blood-cell-associated diseases. In this review, we provide an overview of various fluorescence nanoscopy technologies, outlining their current development stage and the challenges they are facing in terms of functionality and practicality. We specifically explore how these innovations have propelled forward the analysis of thrombocytes (platelets), erythrocytes (red blood cells) and leukocytes (white blood cells), shedding light on the nanoscale arrangement of subcellular components and molecular interactions. We spotlight novel biomarkers uncovered by fluorescence nanoscopy for disease diagnosis, such as thrombocytopathies, malignancies, and infectious diseases. Furthermore, we discuss the technological hurdles and chart out prospective avenues for future research directions. This review aims to underscore the significant contributions of fluorescence nanoscopy to the field of blood cell analysis and disease diagnosis, poised to revolutionize our approach to exploring, understanding, and managing disease at the molecular level.

Breast Implant-Associated Anaplastic Large Cell Lymphoma: Where Hematology and Plastic Surgery Meet.

Breast implant insertion for breast reconstruction or breast augmentation is a developing procedure, with high demand worldwide-being the second most common plastic surgery in the US as of 2022. Breast-implant-associated anaplastic large cell lymphoma (BIA-ALCL) is T-cell, non-Hodgkin lymphoma, typically CD30+, ALK-, presenting with fluid collection in the inner aspect of the peri-implant capsule in most patients, with the onset exceeding 1-year after implantation. The mean time between breast implant insertion and BIA-ALCL development is 7-10 years. The main risk factor is the use of textured implants because of their susceptibility to triggering local inflammation and immune stimulation finally leading to lymphoproliferation. Genetic predispositions to hereditary breast cancer increase the risk of disease development as well. BIA-ALCL seems to be underestimated in many countries and the initial symptom-seroma might be overlooked and misdiagnosed. Despite its rarity, the awareness of the disease should be improved among patients and medical professionals. This paper summarizes epidemiology, etiopathogenesis, differential diagnosis, and treatment-both surgical and hematological approaches.

A comparative study of blood cell count in four automated hematology analyzers: An evaluation of the impact of preanalytical factors.

Differential white blood cell counts are frequently used in diagnosis, patient stratification, and treatment selection to optimize therapy responses. Referral laboratories are often used but challenged with use of different hematology platforms, variable blood shipping times and storage conditions, and the different sensitivities of specific cell types. To extend the scientific literature and knowledge on the temporal commutability of blood samples between hematology analyzers, we performed a comparative ex-vivo study using four of the most utilized commercial platforms, focusing on the assessment of eosinophils given its importance in asthma management. Whole blood from healthy volunteers with and without atopy (n = 6+6) and participants with eosinophilic asthma (n = 6) were stored under different conditions (at 4, 20, 30, and 37°C, with or without agitation) and analyzed at different time points (3, 6, 24, 48 and 72h post-sampling) in parallel on the Abbott CELL-DYN Sapphire, Beckman Coulter DxH900, Siemens ADVIA 2120i and Sysmex XN-1000V. In the same blood samples, eosinophil-derived neurotoxin (EDN), eosinophil activation and death markers were analyzed. All platforms gave comparable measurements of cell differentials on fresh blood within the same day of sampling. However, by 24 hours, significant temporal and temperature-dependent differences were observed, most markedly for eosinophils. None of the platforms performed perfectly across all temperatures tested during the 72 hours, showing that handling conditions should be optimized depending on the cell type of interest and the hematology analyzer. Neither disease status (healthy vs. asthma) nor agitation of the sample affected the cell quantification result or EDN release. The eosinophil activation markers measured by flow cytometry increased with time, were influenced by temperature, and were higher in those with asthma versus healthy participants. In conclusion, hematology analyzer, time window from sampling until analysis, and temperature conditions must be considered when analyzing blood cell differentials, particularly for eosinophils, via central labs to obtain counts comparable to the values obtained in freshly sampled blood.

Enhancing diagnostic accuracy of multiple myeloma through ML-driven analysis of hematological slides: new dataset and identification model to support hematologists.

Multiple Myeloma (MM) is a hematological malignancy characterized by the clonal proliferation of plasma cells within the bone marrow. Diagnosing MM presents considerable challenges, involving the identification of plasma cells in cytology examinations on hematological slides. At present, this is still a time-consuming manual task and has high labor costs. These challenges have adverse implications, which rely heavily on medical professionals' expertise and experience. To tackle these challenges, we present an investigation using Artificial Intelligence, specifically a Machine Learning analysis of hematological slides with a Deep Neural Network (DNN), to support specialists during the process of diagnosing MM. In this sense, the contribution of this study is twofold: in addition to the trained model to diagnose MM, we also make available to the community a fully-curated hematological slide dataset with thousands of images of plasma cells. Taken together, the setup we established here is a framework that researchers and hospitals with limited resources can promptly use. Our contributions provide practical results that have been directly applied in the public health system in Brazil. Given the open-source nature of the project, we anticipate it will be used and extended to diagnose other malignancies.

Pharmacy Workload in Clinical Trial Management: A Preliminary Complexity Assessment Tool for Sponsored Oncology and Haematology Trials.

Investigational drug services need to be organised in a structured approach, especially for sites with a large number of ongoing clinical trials. The aim of this study was to develop a tool to assess the complexity of pharmacy involvement in a sponsored oncology clinical trial. Categorisation into ordinal complexity categories was used to assess the complexity of the clinical trials for consistent pharmacy grant applications. The 15 items of the tool were divided into three sections, and individual item scores were agreed upon among four pharmacists with experience in the conduct of clinical trials at two different centres. A final version of the tool, named Pharm-CAT, was approved. The pharmacists were instructed to use Pharm-CAT to assign a score to each new sponsored trial. To determine the cut-offs for the complexity categories, the scores were sorted in ascending order and the cut-offs corresponding to the first and third tertiles of the score distribution were selected. To verify the reproducibility of the results, Pharm-CAT was applied by two pharmacists independently for each trial. Pharm-CAT proved to be user-friendly. Sixty clinical trials were evaluated and a total of 120 scores were recorded. Low-complexity scores ranged from 0 to 19, medium-complexity scores ranged from 20 to 25, and high-complexity scores were 26 or higher. The average score recorded was 22.88 points. Prospective multicentre validation of Pharm-CAT is needed to confirm its applicability.

Verification of a Benchtop Hematology Analyzer with a 5-Part Differential Count: There is Nothing Wrong with Being Small.

BACKGROUND: The benchtop ADVIA 560 AL hematology analyzer (Siemens Healthineers Tarrytown, NY, USA) offers a small footprint and ease of operation making it suitable for satellite laboratories and intensive care units. A verification study of this analyzer was performed. METHODS: Between- and intra-run precision, carry-over, linearity, and throughput were evaluated on the ADVIA 560 AL. Accuracy was assessed on 94 patient samples by comparing the results obtained on the ADVIA 560 AL to the results on the reference Sysmex XN1000 analyzer (Sysmex Corporation, Kobe, Japan). RESULTS: The ADVIA 560 AL showed acceptable imprecision on control material and minimal bias in comparison to the XN 1000 on patient samples with a throughput of 60 samples per hour. The percentage carryover was not significant and the linearity was within acceptable limits. CONCLUSIONS: The ADVIA 560 AL bench-top analyzer is suitable for acute care centers and satellite laboratories owing to its small footprint, ease of use, and reproducible and accurate results.

Performance evaluation of the Sysmex XN-1000V in side-by-side comparison with the Siemens ADVIA 120 and manual methods for healthy CD Sprague-Dawley rats and CD-1 mice.

BACKGROUND: The Sysmex XN-1000V automated hematology analyzer with multispecies software was released in June 2017 for use in research laboratories. Laser light, impedance, fluorescent staining, and fluorescent flow cytometry are used to analyze whole blood for CBC, reticulocyte counts, and WBC counts, including a 5-part differential leukocyte analysis. OBJECTIVES: A side-by-side comparison of the Sysmex XN-1000V with the Siemens ADVIA 120 in analyzing blood from healthy mice and rats will provide insight into the performance of the new analyzer and its capabilities for use in drug development studies. Method correlation analyses on normal mouse and rat hematology data collected with both analyzers and manual reference methods will help determine the reliability of the data produced using the Sysmex XN-1000V analyzer. METHODS: Whole blood samples collected in K2 EDTA from healthy CD-1 mice and CD Sprague-Dawley rats were analyzed in parallel with the XN-1000V and ADVIA 120 analyzers. Male and female mice, approximately 6-9 weeks old, and male and female rats, approximately 7-9 weeks old, were included in this study. Manual reference methods for WBC differential leukocyte analysis and packed cell volume (PCV) measurements were also performed. EP Evaluator version 11.2 (Data Innovations LLC, South Burlington, VT, USA) was used for method comparison statistical analysis. RESULTS: Most hematologic parameters for naïve mice and rats achieved correlation in the fair to excellent range, with the majority showing very good to excellent correlation with low biases (<11.0%) for cohorts analyzed separately and when cohort data were combined. CONCLUSIONS: The Sysmex XN-1000V Hematology Analyzer provided comparable results to those obtained from the Siemens ADVIA 120. We found the Sysmex XN-1000V Hematology Analyzer to be acceptable for use in drug development studies for rats and mice.

The fully automated Sysmex XN-31 hematology analyzer can detect bloodstream form Trypanosoma brucei.

BACKGROUND: For fully automated detection and quantification of Plasmodium parasites, Sysmex developed the XN-31 hemocytometer. This study investigated whether the XN-31 can also detect and quantify bloodstream form trypanosomes (trypomastigotes). METHODS: Axenic cultures of Trypanosoma brucei brucei were used to prepare two dilution series of trypomastigotes in the whole blood of a healthy donor, which were subsequently examined by the XN-31 as well as by microscopic examination of thin and thick blood films. Trypomastigote intactness during the procedures was evaluated by microscopy. RESULTS: The XN-31 hemocytometer detected trypomastigotes with a detection limit of 26 trypomastigotes/µL. Scattergram patterns of Trypanosoma and Plasmodium parasites were clearly distinct, but current interpretation settings do not allow the identification of trypomastigotes yet, and therefore, need future refinement. CONCLUSION: Proof of concept was provided for an automated fluorescent flow cytometry method that can detect and quantify Plasmodium spp., as well as Trypanosoma brucei trypomastigotes.

Clinical evaluation of a fully electronic microfluidic white blood cell analyzer.

The White Blood Cell (WBC) count is one of the key parameters signaling the health of the immune system. Abnormal WBC counts often signal a systemic insult to the body such as an underlying infection or an adverse side effect to medication. Typically, the blood collected is sent to a central lab for testing, and results come back within hours, which is often inconvenient and may delay time-sensitive diagnosis or treatment. Here, we present the CytoTracker, a fully electronic, microfluidic based instant WBC analyzer with the potential to be used at point-of-care. The CytoTracker is a lightweight, portable, affordable platform capable of quantifying WBCs within minutes using only 50 µl of blood (approximately one drop of blood). In this study, we clinically evaluated the accuracy and performance of CytoTracker in measuring WBC and granulocyte counts. A total of 210 adult patients were recruited in the study. We validated the CytoTracker against a standard benchtop analyzer (Horiba Point of Care Hematology Analyzer, ABX Micros 60). Linear dynamic ranges of 2.5 k/µl- 35 k/µl and 0.6 k/µl- 26 k/µl were achieved for total WBC count and granulocyte count with correlation coefficients of 0.97 and 0.98. In addition, we verified CytoTracker's capability of identifying abnormal blood counts with above 90% sensitivity and specificity. The promising results of this clinical validation study demonstrate the potential for the use of the CytoTracker as a reliable and accurate point-of-care WBC analyzer.

Performance evaluation the new automated Atellica Hema 580 hematology analyzer.

INTRODUCTION: The Atellica Hema (Siemens Healthineers, Tarrytown, NY, USA) is a new generation multi-parameter analyzer for full blood count, 6-part differential and reticulocyte testing by impedance variation and fluorescence flow cytometry. In this study, we verified the whole blood and limited body fluid modes of the Atellica Hema 580. METHODS: We evaluated precision, linearity, carry-over, throughput and performed a method comparison to assess the performance of the Atellica Hema 580. For comparison of the Atellica Hema 580 with the Sysmex XN-1000 (Sysmex, Kobe, Japan), 140 samples from adult and pediatric patients including both normal and abnormal hematology profiles were analyzed in parallel. RESULTS: The Atellica Hema 580 demonstrated acceptable imprecision within the manufacturer's specifications for whole blood and body fluid modes, good linearity for high and low ranges and no significant carryover. The full blood count, differential and reticulocyte correlated well with the Sysmex XN-1000, except for mean cell hemoglobin concentration, basophil and large immature cells. The optical platelet count, reflexed in 34 samples with a platelet count <150 × 109 /l, showed a strong correlation with the fluorescent platelet count on the Sysmex XN-1000. The morphology flagging efficiency was 92% for white blood cells, 95% for red blood cells and 87% for platelets. CONCLUSION: The Atellica Hema 580 showed good analytical performance and workflow efficiency for a wide range of patient samples.

Performance evaluation of alternate ESR measurement method using BC-780 automated hematology analyzer: a comparison study with the Westergren reference method.

OBJECTIVES: Implementation of alternate erythrocyte sedimentation rate (ESR) measurement method is increasing worldwide due to its various advantages. In this study, we aim to evaluate the analytical performance of the BC-780 automated hematology analyzer in measurement of ESR value. METHODS: Analyzer performance including precision study, carryover, sample stability and potential interferences are examined. Samples with ESR values spanning the whole analytical ESR range are included for method comparison study. Samples with different hematocrit (Hct) and mean corpuscular volume (MCV) values are also analyzed and compared with the results obtained from the Westergren reference method. RESULTS: Precisions and carryover results are consistent with the manufacturers' claim. ESR values do not change significantly in the samples stored at 2-8 °C for 24 h (h) or at room temperature (RT) for 8 h, but significantly decreased (p<0.001) when stored at RT for 24 h. Significant increase in ESR value is documented in samples that are hemolyzed (hemoglobin concentration ranged from 1.28-6.01 g/L) (p=0.010) or lipemic (triglyceride above 4.75 mmol/L) (p=0.001). Method comparison study yields a proportional difference with a regression equation=3.08+ 0.98x. Bland-Altman analysis shows a mean absolute bias of 3.12 mm. The obtained absolute mean biases are below 5 mm in all analytical categories except for the group where MCV>100 fL. CONCLUSIONS: Most tested parameters met the manufacturer's specifications and were comparable to the reference method. Despite the presence of positive bias, it falls within acceptable criteria. Extensive validation against potential interferences such as hemolysis/lipemia is still necessary in future.

Performance evaluation of a novel platelet count parameter, hybrid platelet count, on the BC-780 automated hematology analyzer.

OBJECTIVES: Automated hematology analysis is expected to improve the performance of platelet counting. We evaluated the performance of a new platelet counting, hybrid (PLT-H) and also impedance (PLT-I) and optical (PLT-O) on the BC-780 automated hematology analyzer compared to the international reference method (IRM) in blood samples with thrombocytopenic and platelet interference. METHODS: The basic platelet count performance of the BC-780 automated hematology analyzer was evaluated according to the requirements of the Clinical Laboratory and Standards Institute (CLSI) Document H26-A2. Additionally, the thrombocytopenic (low PLT count) blood samples and the platelet interference blood samples including fragmented red blood cells (RBCs), microcytes or small RBCs, and giant platelets were determined with the BC-780 hematology analyzer compared to the IRM. RESULTS: Blank counting and the carry-over contamination rate of platelet count using the BC-780 both met the manufacturers' claim. For both 123 thrombocytopenic and 232 platelet interference blood samples (72 fragmented RBCs, 91 microcytes and 51 giant platelets), all three platelet counting methods exhibited high comparability with the IRM (the lowest correlation (r)=0.916). Interestingly, the comparability of PLT-H (r=0.928-0.986) with the IRM was better than that of PLT-I (r=0.916-0.979). CONCLUSIONS: The performance of PLT-H in the BC-780 met the manufacturer's specifications. PLT-H exhibits better reproducibility than did PLT-I, correlates well with the PLT-O for thrombocytopenic samples and demonstrates good anti-interference ability. PLT-H counting is therefore recommended as a zero-cost alternative platelet counting method for platelet interference samples in clinical settings.

Validation of a hematology analyzer in donkey medicine.

Asinina de Miranda is a protected donkey sub-species from the Mirandês plateau in northeastern of Portugal. Donkeys are animals that have substantially lost their place as working animals in modern society, this had led to a decrease in their population numbers. A need to preserve native species has led to the foundation of organizations like Associação para o Estudo e Proteção do Gado Asinino (AEPGA) and the development of studies regarding breed welfare, such as hematology. The IDEXX ProCyte Dx is a veterinary hematology analyzer validated for several species, but not for donkeys. The aim of this study was to validate the ProCyte Dx for Asinina de Miranda donkeys. The validation requires a controlled study of precision, carryover, linearity and comparison between the equipment and the manually obtained values for the leukocyte differential count and hematocrit. Results indicated coefficient of variation was good (below 5 %) for both the intra-assay and the inter-assay precision, except for basophils. Carryover was 0 % for all the parameters except platelets (5.88 %). Linearity showed a very high Pearson correlation coefficient, above 0.99, for erythrocytes, hematocrit, hemoglobin, leucocytes, neutrophils, lymphocytes, monocytes, eosinophils, platelets and plateletcrit. Comparison demonstrated excellent agreement for hematocrit (rs=0.96) and good Spearman rank correlation for neutrophils (rs=0.84) and lymphocytes (rs=0.90). Accuracy for total leukocyte count and platelets could not be determined. In conclusion, the ProCyte Dx seems appropriate to be used in Asinina de Miranda hematology.

Personalized and Population-Based Reference Intervals for 48 Common Clinical Chemistry and Hematology Measurands: A Comparative Study.

BACKGROUND: Personalized reference intervals (prRIs) have the potential to improve individual patient follow-up as compared to population-based reference intervals (popRI). In this study, we estimated popRI and prRIs for 48 clinical chemistry and hematology measurands using samples from the same reference individuals and explored the effect of using group-based and individually based biological variation (BV) estimates to derive prRIs. METHODS: 143 individuals (median age 28 years) were included in the study and had fasting blood samples collected once. From this population, 41 randomly selected subjects had samples collected weekly for 5 weeks. PopRIs were estimated according to Clinical Laboratory Standards Institute EP28 and within-subject BV (CVI) were estimated by CV-ANOVA. Data were assessed for trends and outliers prior to calculation of individual prRIs, based on estimates of (a) within-person BV (CVP), (b) CVI derived in this study, and (c) publically available CVI estimates. RESULTS: For most measurands, the individual prRI ranges were smaller than the popRI range, but overall about half the study participants had a prRI wider than the popRI for 5 or more out of 48 measurands. The dispersion of prRIs based on CVP was wider than that of prRIs based on CVI. CONCLUSION: The prRIs derived in our study varied significantly between different individuals, especially if based on CVP. Our results highlight the limitations of popRIs in interpreting test results of individual patients. If sufficient data from a steady-state situation are available, using prRI based on CVP estimates will provide a RI most specific for an individual patient.

Reference intervals for reticulocyte indices, immature reticulocyte fraction, and the percentage of hypochromic red blood cells in adult large breed dogs using the ADVIA 2120 hematology analyzer.

Reticulocyte indices are used to characterize anemia, including the identification of regeneration. In people, the immature reticulocyte fraction (IRF), percentage of hypochromic red blood cells (%HYPO-RBC), and other reticulocyte indices have been used as earlier indicators of erythropoiesis and as valuable monitoring tools in the assessment of various therapies. The reference intervals (RI) of the IRF and %HYPO-RBC have not been reported in dogs. The objective of this study was to establish RIs for novel variables (IRF, %HYPO-RBC, and CH-delta) and assess RIs for more commonly reported reticulocyte indices in healthy dogs. RIs were calculated from blood results retrospectively collected from 106 client-owned healthy dogs at the time of induction into a blood donor program using the ADVIA 2120 hematology analyzer (Siemens Healthcare Diagnostics). For the calculation of RIs, appropriate tests were applied for outlier detection and normality assessment. For variables normally distributed, RIs and their respective 90% confidence intervals (CIs) were calculated using parametric methods, while for variables not normally distributed, robust methods were used and bootstrapping for calculating the 90% CIs. The following RIs were established: reticulocyte hemoglobin content (CHr) 24.5-28 pg, mean reticulocyte volume (MCVr) 85.9-99.3 fL, mean corpuscular hemoglobin concentration of reticulocytes (CHCMr) 271.0-306.3 g/L, IRF 10.4%-43.5%, CH-delta 0.5-4.3 pg, and percentage of hypochromic red blood cells (%HYPO-RBC) 0.10%-0.80%. The results of this study provide RIs for novel reticulocyte variables. Further studies are required to determine the clinical utility of IRF, %HYPO-RBC, and CH delta as early indicators of erythropoietic activity in canine patients.

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.

Effective and Practical Complete Blood Count Delta Check Method and Criteria for the Quality Control of Automated Hematology Analyzers.

Background: Delta checks increase patient safety by identifying automated hematology analyzer errors. International standards and guidelines for the complete blood count (CBC) delta check method have not been established. We established an effective, practical CBC delta check method and criteria. Methods: We assessed five delta check methods for nine CBC items (Hb, mean corpuscular volume, platelet count, white blood cell [WBC] count, and five-part WBC differential counts) using 219,804 blood samples from outpatients and inpatients collected over nine months. We adopted the best method and criteria and evaluated them using 42,652 CBC samples collected over two weeks with a new workflow algorithm for identifying test errors and corrections for Hb and platelet count. Results: The median delta check time interval was 1 and 21 days for inpatients and outpatients (range, 1-20 and 1-222 days), respectively. We used delta values at 99.5% as delta check criteria; the criteria varied among the five methods and between outpatients and inpatients. The delta percent change (DPC)/reference range (RR) rate performed best as the delta check for CBC items. Using the new DPC/RR rate method, 1.7% of total test results exceeded the delta check criteria; the retesting and resampling rates were 0.5% and 0.001%, respectively. Conclusions: We developed an effective, practical delta check method, including RRs and delta check time intervals, and delta check criteria for nine CBC items. The criteria differ between outpatients and inpatients. Using the new workflow algorithm, we can identify the causes of criterion exceedance and report correct test results.

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.