Purpose and criteria for blood smear scan, blood smear examination, and blood smear review

Clinician-Ordered Peripheral Smear Review by a Pathologist Has Low Clinical Utility-A Reference Laboratory Perspective

BACKGROUND

Clinician-ordered peripheral smear review by pathologist (CPSR) is commonly ordered and has been recommended for decades. However, the clinical utility of this labor-intensive test in the reference laboratory has not been examined. The objective of this study is to assess hematologic abnormalities identified in CPSR orders and to correlate them with complete blood count (CBC) and laboratory-derived smear review (LDSR) in the reference laboratory.

METHODS

Two hundred consecutive CPSRs with corresponding CBCs from April 2023 were run by Sysmex® XN-11 analyzers, and their peripheral smears were examined by a board-certified hematopathologist. Hematologic abnormalities of CPSRs were assessed, and the correlation between CPSR and CBC/LDSR was reviewed.

RESULTS

Nearly one-third of CPSRs (29%) had normal peripheral smears and CBCs. The majority of CPSRs showed nonspecific quantitative abnormalities. When compared against CPSR results, LDSR criteria identified 100% of hematologic abnormalities appropriately. Samples that were not flagged for review by LDSR rules were also reviewed (n = 174) to rule out clinically meaningful false negatives. One minor discrepancy (0.6% of cases) of small platelet aggregates was observed in a patient with a reported platelet count of 139 K/uL that was missed by the LDSR process.

CONCLUSIONS

In the reference laboratory setting, our findings demonstrate that LDSR adequately detects significant hematologic abnormalities and, therefore, CPSR should be discontinued.

Application of image recognition technology in pathological diagnosis of blood smears

Traditional manual blood smear diagnosis methods are time-consuming and prone to errors, often relying heavily on the experience of clinical laboratory analysts for accuracy. As breakthroughs in key technologies such as neural networks and deep learning continue to drive digital transformation in the medical field, image recognition technology is increasingly being leveraged to enhance existing medical processes. In recent years, advancements in computer technology have led to improved efficiency in the identification of blood cells in blood smears through the use of image recognition technology. This paper provides a comprehensive summary of the methods and steps involved in utilizing image recognition algorithms for diagnosing diseases in blood smears, with a focus on malaria and leukemia. Furthermore, it offers a forward-looking research direction for the development of a comprehensive blood cell pathological detection system.

Clinical decision support to improve CBC and differential ordering

OBJECTIVES

Complete blood count and differential (CBC diff) is a common laboratory test that may be overused or misordered, particularly in an inpatient setting. We assessed the ability of a clinical decision support (CDS) alert to decrease unnecessary orders for CBC diff and analyzed its impact in the laboratory.

METHODS

We designed 3 CDS alerts to provide guidance to providers ordering CBC diff on inpatients at frequencies of daily, greater than once daily, or as needed.

RESULTS

The 3 alerts were highly effective in reducing orders for CBC diff at the frequencies targeted by the alert. Overall, test volume for CBC diff decreased by 32% (mean of 5257 tests per month) after implementation of the alerts, with a corresponding decrease of 22% in manual differentials performed (mean of 898 per month). Turnaround time for manual differentials decreased by a mean of 41.5 minutes, with a mean decrease of up to 90 minutes during peak morning hours.

CONCLUSIONS

The 3 CDS alerts successfully decreased inpatient orders for CBC diff and improved the quality of patient care by decreasing turnaround time for manual differentials.

Evaluating pathologist practices in peripheral blood smear review: A comprehensive practice survey

OBJECTIVES

Widely accepted standardized criteria for peripheral blood (PB) smear review do not exist. The aim of this study was to collect data regarding PB smear review practices across multiple institutions, with a focus on pathologist review.

METHODS

A 23-question survey was developed by members of the Society for Hematopathology (SH) Education Committee and distributed to SH members. The survey included questions on practice environment and PB smear review practices, including trainee involvement.

RESULTS

Of 725 members contacted, 137 (19%) completed the entire survey. Over half of practices examined 5 to 20 smears a day. All respondents reported using complete blood count/differential leukocyte count data and clinical history as part of smear review. The reported proportion of laboratory-initiated vs clinician-requested reviews varied across respondents. Clinician-requested smear reviews were more likely to be billed and issued as a separate pathology report. Glass slide review (as opposed to digital microscopy) was used by most respondents. All respondents affirmed that PB smear review is an essential component of pathology training programs. Numerous free-text comments were submitted by respondents regarding their own experiences with PB smear review and suggested improvements.

CONCLUSIONS

This survey elucidated the spectrum of practice patterns for pathologist review of blood smears and identified potential areas for process improvement.

1 Million Segmented Red Blood Cells With 240 K Classified in 9 Shapes and 47 K Patches of 25 Manual Blood Smears

Around 20% of complete blood count samples necessitate visual review using light microscopes or digital pathology scanners. There is currently no technological alternative to the visual examination of red blood cells (RBCs) morphology/shapes. True/non-artifact teardrop-shaped RBCs and schistocytes/fragmented RBCs are commonly associated with serious medical conditions that could be fatal, increased ovalocytes are associated with almost all types of anemias. 25 distinct blood smears, each from a different patient, were manually prepared, stained, and then sorted into four groups. Each group underwent imaging using different cameras integrated into light microscopes with 40X microscopic lenses resulting in total 47 K + field images/patches. Two hematologists processed cell-by-cell to provide one million + segmented RBCs with their XYWH coordinates and classified 240 K + RBCs into nine shapes. This dataset (Elsafty_RBCs_for_AI) enables the development/testing of deep learning-based (DL) automation of RBCs morphology/shapes examination, including specific normalization of blood smear stains (different from histopathology stains), detection/counting, segmentation, and classification. Two codes are provided (Elsafty_Codes_for_AI), one for semi-automated image processing and another for training/testing of a DL-based image classifier.

Detection of blasts using flags and cell population data rules on Beckman Coulter DxH 900 hematology analyzer in patients with hematologic diseases

OBJECTIVES

White blood cell (WBC)-related flags are essential for detecting abnormal cells including blasts in automated hematology analyzers (AHAs). Cell population data (CPD) may characterize each WBC population, and customized CPD rules can be also useful for detecting blasts. We evaluated the performance of WBC-related flags, customized CPD rules, and their combination for detecting blasts on the Beckman Coulter DxH 900 AHA (DxH 900, Beckman Coulter, Miami, Florida, USA).

METHODS

In a total of 239 samples from patients with hematologic diseases, complete blood count on DxH 900 and manual slide review (MSR) were conducted. The sensitivity, specificity, and efficiency of the five WBC-related flags, nine customized CPD rules, and their combination were evaluated for detecting blasts, in comparison with MSR.

RESULTS

Blasts were detected by MSR in 40 out of 239 (16.7 %) samples. The combination of flags and CPD rules showed the highest sensitivity compared with each of flags and CPD rules for detecting blasts (97.5 vs. 72.5 % vs. 92.5 %). Compared with any flag, the combination of flags and CPD rules significantly reduced false-negative samples from 11 to one for detecting blasts (27.5 vs. 2.5 %, p=0.002).

CONCLUSIONS

This is the first study that evaluated the performance of both flags and CPD rules on DxH 900. The customized CPD rules as well as the combination of flags and CPD rules outperformed WBC-related flags for detecting blasts on DxH 900. The customized CPD rules can play a complementary role for improving the capability of blast detection on DxH 900.

Performance of the digital cell morphology analyzer MC-100i in a multicenter study in tertiary hospitals in China

BACKGROUND

This study investigated the performance of the MC-100i, a pre-commercial digital morphology analyzer utilizing a convolutional neural network algorithm, in a multicentric setting involving up to 11 tertiary hospitals in China.

METHODS

Blood smears were analyzed by MC-100i, verified by morphologists, and manually differentiated. The classification performance on WBCs and RBCs was evaluated by comparing the classification results using different methods. The PLT and PLT clump counting performance was also assessed. The total assay time including hands-on time was evaluated.

RESULTS

The agreements between pre- and post-classification were high for normal WBCs (κ > 0.96) and lower for overall abnormal WBCs (κ = 0.90). The post-classification results correlated well with manual differentials for both normal and abnormal WBCs (r > 0.93), except for basophils (r = 0.8480) and atypical lymphocytes (r = 0.8211). The clinical sensitivity and specificity of each RBC abnormality after verification were above 90 % using microscopy reviews as the reference. The PLTs counted by the MC-100i before and after verification correlated well with those measured by the PLT-O mode (r = 0.98). Moreover, PLT clumps were successfully classified by the analyzer in EDTA-dependent pseudothrombocytopenia blood samples.

CONCLUSIONS

The MC-100i is an accurate and reliable digital cell morphology analyzer, offering another intelligent option for hematology laboratories.

White blood cells classification using multi-fold pre-processing and optimized CNN model

White blood cells (WBCs) play a vital role in immune responses against infections and foreign agents. Different WBC types exist, and anomalies within them can indicate diseases like leukemia. Previous research suffers from limited accuracy and inflated performance due to the usage of less important features. Moreover, these studies often focus on fewer WBC types, exaggerating accuracy. This study addresses the crucial task of classifying WBC types using microscopic images. This study introduces a novel approach using extensive pre-processing with data augmentation techniques to produce a more significant feature set to achieve more promising results. The study conducts experiments employing both conventional deep learning and transfer learning models, comparing performance with state-of-the-art machine and deep learning models. Results reveal that a pre-processed feature set and convolutional neural network classifier achieves a significantly better accuracy of 0.99. The proposed method demonstrates superior accuracy and computational efficiency compared to existing state-of-the-art works.

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

INTRODUCTION

Mindray MC-80 is an automated system for digital imaging of white blood cells (WBCs) and their pre-classification. The objective of this work is to analyse its performance comparing it with the CellaVision® DM9600.

METHODS

A total of 445 samples were used, 194 normal and 251 abnormal: acute leukaemia (100), myelodysplastic syndromes/myeloproliferative neoplasms (33), lymphoid neoplasms (50), plasma cell neoplasms (14), infections (49) and thrombocytopenia (5). WBC pre-classification values with the MC-80 and DM9600 were compared with (1) the microscope, (2) Mindray BC-6800Plus differentials in only normal samples, and (3) confirmed or reclassified images (post-classification). Pearson's correlation, Lin's concordance, Passing-Bablok regression, and Bland-Altman plots were used. Sensitivity, specificity, positive (PPV) and negative (NPV) predictive values for abnormal cells using the MC-80 were calculated.

RESULTS

The PPV and NPV were above 98% and 99%, for normal samples. For immature granulocytes (IG), NPV and PPV were 100% and 74.2%. When comparing the WBC differentials using the MC-80, the microscope and the BC-6800Plus, no differences were found except for basophils and IG. Our results showed good agreement between the pre- and post-classification of normal WBC, including IG, quantified by high correlation and concordance values (0.91-1). Sensitivity and specificity for blasts were 0.984 and 0.640. The MC-80 detected abnormal lymphocytes in 30% of the smears from patients with lymphoid neoplasm. Plasma cell identification was better using the DM9600. The sensitivity and specificity for erythroblast detection were 1 and 0.890.

CONCLUSION

We found that the MC-80 shows high performance for WBC differentials for both normal samples and patients with haematological diseases.

Unraveling the motion and deformation characteristics of red blood cells in a deterministic lateral displacement device

Deterministic Lateral Displacement (DLD) device has gained widespread recognition and trusted for filtering blood cells. However, there remains a crucial need to explore the complex interplay between deformable cells and flow within the DLD device to improve its design. This paper presents an approach utilizing a mesoscopic cell-level numerical model based on dissipative particle dynamics to effectively capture this complex phenomenon. To establish the model's credibility, a series of numerical simulations were conducted and the numerical results were validated with nominal experimental data from the literature. These include single cell stretching experiment, comparisons of the morphological characteristics of cells in DLD, and comparison the specific row-shift fraction of DLD required to initiate the zigzag mode. Additionally, we investigate the effect of cell rigidity, which serves as an indicator of cell health, on average flow velocity, trajectory, and asphericity. Moreover, we extend the existing theory of predicting zigzag mode for solid spherical particles to encompass the behavior of red blood cells. To achieve this, we introduce a new concept of effective diameter and demonstrate its applicability in providing highly accurate predictions across a wide range of conditions.

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.

RPA/CRISPR-cas12a as a specific, sensitive and rapid method for diagnosing Ehrlichia canis and Anaplasma platys in dogs in Thailand

Rickettsial pathogens including Ehrlichia canis and Anaplasma platys are bacteria that cause parasitic infections in dogs such as canine monocytic ehrlichiosis (CME) and canine cyclic thrombocytopenia (CCT), respectively affecting mortality and morbidity worldwide. An accurate, sensitive, and rapid method to diagnose these agents is essential for effective treatment. In this study, a recombinase polymerase amplification (RPA) coupled with CRISPR-Cas12a methods was established to detect E. canis and A. platys infection in dogs based on the 16S rRNA. The optimal condition for DNA amplification by RPA was 37 °C for 20 min, followed by CRISPR-Cas12a digestion at 37 °C for one hour. A combination of RPA and the cas12a detection method did not react with other pathogens and demonstrated strong sensitivity, detecting as low as 100 copies of both E. canis and A. platys. This simultaneous detection method was significantly more sensitive than conventional PCR. The RPA-assisted cas12a assay provides specific, sensitive, rapid, simple and appropriate detection of rickettsial agents in canine blood at the point-of-care for diagnostics, disease prevention and surveillance.

Eosinophils as potential biomarkers in respiratory viral infections

Eosinophils are bone marrow-derived granulocytes that, under homeostatic conditions, account for as much as 1-3% of peripheral blood leukocytes. During inflammation, eosinophils can rapidly expand and infiltrate inflamed tissues, guided by cytokines and alarmins (such as IL-33), adhesion molecules and chemokines. Eosinophils play a prominent role in allergic asthma and parasitic infections. Nonetheless, they participate in the immune response against respiratory viruses such as respiratory syncytial virus and influenza. Notably, respiratory viruses are associated with asthma exacerbation. Eosinophils release several molecules endowed with antiviral activity, including cationic proteins, RNases and reactive oxygen and nitrogen species. On the other hand, eosinophils release several cytokines involved in homeostasis maintenance and Th2-related inflammation. In the context of SARS-CoV-2 infection, emerging evidence indicates that eosinophils can represent possible blood-based biomarkers for diagnosis, prognosis, and severity prediction of disease. In particular, eosinopenia seems to be an indicator of severity among patients with COVID-19, whereas an increased eosinophil count is associated with a better prognosis, including a lower incidence of complications and mortality. In the present review, we provide an overview of the role and plasticity of eosinophils focusing on various respiratory viral infections and in the context of viral and allergic disease comorbidities. We will discuss the potential utility of eosinophils as prognostic/predictive immune biomarkers in emerging respiratory viral diseases, particularly COVID-19. Finally, we will revisit some of the relevant methods and tools that have contributed to the advances in the dissection of various eosinophil subsets in different pathological settings for future biomarker definition.

Accurate stratification between VEXAS syndrome and differential diagnoses by deep learning analysis of peripheral blood smears

OBJECTIVES

VEXAS syndrome is a newly described autoinflammatory disease associated with UBA1 somatic mutations and vacuolization of myeloid precursors. This disease possesses an increasingly broad spectrum, leading to an increase in the number of suspected cases. Its diagnosis via bone-marrow aspiration and UBA1-gene sequencing is time-consuming and expensive. This study aimed at analyzing peripheral leukocytes using deep learning approaches to predict VEXAS syndrome in comparison to differential diagnoses.

METHODS

We compared leukocyte images from blood smears of three groups: participants with VEXAS syndrome (identified UBA1 mutation) (VEXAS); participants with features strongly suggestive of VEXAS syndrome but without UBA1 mutation (UBA1-WT); participants with a myelodysplastic syndrome and without clinical suspicion of VEXAS syndrome (MDS). To compare images of circulating leukocytes, we applied a two-step procedure. First, we used self-supervised contrastive learning to train convolutional neural networks to translate leukocyte images into lower-dimensional encodings. Then, we employed support vector machine to predict patients' condition based on those leukocyte encodings.

RESULTS

The VEXAS, UBA1-WT, and MDS groups included 3, 3, and 6 patients respectively. Analysis of 33,757 images of neutrophils and monocytes enabled us to distinguish VEXAS patients from both UBA1-WT and MDS patients, with mean ROC-AUCs ranging from 0.87 to 0.95.

CONCLUSIONS

Image analysis of blood smears via deep learning accurately distinguished neutrophils and monocytes drawn from patients with VEXAS syndrome from those of patients with similar clinical and/or biological features but without UBA1 mutation. Our findings offer a promising pathway to better screening for this disease.

Digital assessment of peripheral blood and bone marrow aspirate smears

The diagnosis of benign and neoplastic hematologic disorders relies on analysis of peripheral blood and bone marrow aspirate smears. As demonstrated by the widespread laboratory adoption of hematology analyzers for automated assessment of peripheral blood, digital analysis of these samples provides many significant benefits compared to relying solely on manual review. Nonetheless, analogous instruments for digital bone marrow aspirate smear assessment have yet to be clinically implemented. In this review, we first provide a historical overview detailing the implementation of hematology analyzers for digital peripheral blood assessment in the clinical laboratory, including the improvements in accuracy, scope, and throughput of current instruments over prior generations. We also describe recent research in digital peripheral blood assessment, particularly in the development of advanced machine learning models that may soon be incorporated into commercial instruments. Next, we provide an overview of recent research in digital assessment of bone marrow aspirate smears and how these approaches could soon lead to development and clinical adoption of instrumentation for automated bone marrow aspirate smear analysis. Finally, we describe the relative advantages and provide our vision for the future of digital assessment of peripheral blood and bone marrow aspirate smears, including what improvements we can soon expect in the hematology laboratory.

Hilab System Device in an Oncological Hospital: A New Clinical Approach for Point of Care CBC Test, Supported by the Internet of Things and Machine Learning

The complete blood count (CBC) is a highly requested test that is generally restricted to centralized laboratories, which are limited by high cost, being maintenance-demanding, and requiring costly equipment. The Hilab System (HS) is a small, handheld hematological platform that uses microscopy and chromatography techniques, combined with machine learning (ML) and artificial intelligence (AI), to perform a CBC test. This platform uses ML and AI techniques to add higher accuracy and reliability to the results besides allowing for faster reporting. For clinical and flagging capability evaluation of the handheld device, the study analyzed 550 blood samples of patients from a reference institution for oncological diseases. The clinical analysis encompassed the data comparison between the Hilab System and a conventional hematological analyzer (Sysmex XE-2100) for all CBC analytes. The flagging capability study compared the microscopic findings from the Hilab System and the standard blood smear evaluation method. The study also assessed the sample collection source (venous or capillary) influences. The Pearson correlation, Student t-test, Bland-Altman, and Passing-Bablok plot of analytes were calculated and are shown. Data from both methodologies were similar (p > 0.05; r ≥ 0.9 for most parameters) for all CBC analytes and flagging parameters. Venous and capillary samples did not differ statistically (p > 0.05). The study indicates that the Hilab System provides humanized blood collection associated with fast and accurate data, essential features for patient wellbeing and quick physician decision making.

Evaluation of the WBC-differential flagging performances and accuracy of the HORIBA Yumizen H2500 cell counter in oncology patients from a single institution

INTRODUCTION

The Yumizen H2500 (YH2500) cell analyser was compared to the Pentra DX Nexus (both from HORIBA Medical) to evaluate the efficiency of the new YH2500 technology for the WBC-differential in samples from oncology patients with WBC-diff abnormalities.

MATERIAL AND METHODS

The 220 samples with slide review criteria on the Nexus were systematically analysed on the YH2500. The WBC-diff was compared to flow cytometry (FCM). The 100 additional samples with Monocyte/Neutrophil separation flags were evaluated. The flagging performance and the accuracy of the WBC-diff were analysed.

RESULTS

The YH2500 generated fewer flags than the Nexus (47.73% vs 66.64%; p < .0001), except for Monocyte/Neutrophil flag (15.5% vs. 2.7%; p < 0.0001). Overall performances were higher on the YH2500 (Sensitivity, 100 vs. 89.6%; Specificity 81.0% vs. 50.9%; PPV, 74.3% vs. 62.9%; NPV, 100% vs. 69.5%; Efficiency, 87.7% vs. 69.5%). YH2500 showed a statistically significant better correlation with FCM for the 6-part differential than the Nexus. On 134 samples with Monocyte/Neutrophil separation flag, it was shown that, in samples with less than 10% monocytes on the YH2500, the results of monocyte and neutrophil counts were comparable to the manual count, and that these samples did not need a slide review if no other main criterion for review was present.

CONCLUSION

The YH2500 demonstrated better performance characteristics than the previous cell counter, the Nexus. Its implementation in our laboratory routine work significantly improved the practice workflow, decreased the number of manual cell counts and increased the pertinence of slide review and reporting of the microscopic count.

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.

A multiple instance learning approach for detecting COVID-19 in peripheral blood smears

A wide variety of diseases are commonly diagnosed via the visual examination of cell morphology within a peripheral blood smear. For certain diseases, such as COVID-19, morphological impact across the multitude of blood cell types is still poorly understood. In this paper, we present a multiple instance learning-based approach to aggregate high-resolution morphological information across many blood cells and cell types to automatically diagnose disease at a per-patient level. We integrated image and diagnostic information from across 236 patients to demonstrate not only that there is a significant link between blood and a patient's COVID-19 infection status, but also that novel machine learning approaches offer a powerful and scalable means to analyze peripheral blood smears. Our results both backup and enhance hematological findings relating blood cell morphology to COVID-19, and offer a high diagnostic efficacy; with a 79% accuracy and a ROC-AUC of 0.90.

Automatic analysis system for abnormal red blood cells in peripheral blood smears

The type and ratio of abnormal red blood cells (RBCs) in blood can be identified through peripheral blood smear test. Accurate classification is important because the accompanying diseases indicated by abnormal RBCs vary. In clinical practice, this task is time-consuming because the RBCs are manually classified. In addition, because the classification depends on the subjective criteria of pathologists, objective classification is difficult to achieve. In this paper, an automatic classification method that is solely based on images of RBCs captured under a microscope and processed using machine learning (ML) is proposed. The size and hemoglobin abnormalities of RBCs were classified by optimizing the criteria used in clinical practice. For morphologically abnormal RBCs classification, used seven geometric features information (major axis, minor axis, ratio of major and minor axis, perimeter, circularity, number of convex hulls, difference between area and convex area) and five types of multiple classifiers (Support Vector Machine, Decision Tree, K-Nearest Neighbor, Random Forest, and Adaboost models). Among was categorized using SVM, highly accurate results (99.9%) were obtained. The classification is performed simultaneously, and results are provided to the user through a graphical user interface (GUI).

Fast, Reusable, Cell Uniformly Distributed Membrane Filtration Device for Separation of Circulating Tumor Cells

Isolation of circulating tumor cells (CTCs) is of great significance for the diagnosis, prognosis, and treatment of metastatic cancer. Among CTC capture methods independent of antibodies, membrane filtration-based methods have the advantages of simplicity, rapidity, and high throughput but usually have problems such as clogging, high pressure drop, and impaired cell viability. In this study, we designed and tested a reusable device that used horizontal rotor and fluid-assisted separation to capture CTCs by centrifugal membrane filtration, achieving simple, fast, highly efficient, and viable cell capture on traditional centrifuge. The average capture efficiency was 95.8% for different types of cancer cells with >90% survival, and the removal of white blood cells can reach 99.72% under four times cleaning of the membrane after filtration. A further clinic demo was performed using the device to detect residual leukemic cells in patients; the results showed a 10-fold enrichment of the leukemic cells in peripheral blood samples. Taken together, the simple, robust, and efficient CTC capture device may have the potential for clinic routine detection and analysis of circulating tumor cells.

Optimizing rat and human blood cells sampling for in silico morphometric analysis

Measurements of Morphometric Parameters of the Blood Cells (MPBC) are key for the diagnosis of both mental and metabolic diseases. Several manual approaches or computational methodologies are useful to provide reliable clinical diagnosis. The sample processing and data analysis is relevant, however the sample handling on the pre-analytical phase remains scarcely evaluated. The main goal of this study was to favor the preservation of blood smear using a histological resin. This strategy lead us two practical approaches, give a detailed morphometric description of white blood cells and establish reference intervals in male Wistar rats, which are scarcely reported. Blood smears from male Wistar rats (n = 120) and adult men were collected at room temperature. The integrity of Wright-stained cells was evaluated by an in silico image analysis from rat and human blood smear preserved with a toluene-based synthetic resin mounting medium. A single sample of human blood was used as a control of procedure. The reference intervals was established by cell counting. Based on the results of segmentation algorithm followed by an automatic thresholding analysis, the incorporation of resin favor the conservation of cell blood populations, and lead to identify morphologic features such as nucleus/cytoplasmic shape, granules presence and DNA appearance in nucleus of white blood cells. The use of a histological resin could favor a fast and efficient sample handling in silico MPBC measurements both in the species studied as in wild animals.

Blood Cell Analysis: From Traditional Methods to Super-Resolution Microscopy

Blood cell analysis is essential for the diagnosis and identification of hematological malignancies. The use of digital microscopy systems has been extended in clinical laboratories. Super-resolution microscopy (SRM) has attracted wide attention in the medical field due to its nanoscale spatial resolution and high sensitivity. It is considered to be a potential method of blood cell analysis that may have more advantages than traditional approaches such as conventional optical microscopy and hematology analyzers in certain examination projects. In this review, we firstly summarize several common blood cell analysis technologies in the clinic, and analyze the advantages and disadvantages of these technologies. Then, we focus on the basic principles and characteristics of three representative SRM techniques, as well as the latest advances in these techniques for blood cell analysis. Finally, we discuss the developmental trend and possible research directions of SRM, and provide some discussions on further development of technologies for blood cell analysis.

Sustainable Laboratory-Driven Method to Decrease Repeat, Same-Day WBC Differentials at a Tertiary Care Center

OBJECTIVES

A CBC with WBC differential is often ordered when a CBC alone would be sufficient for patient care. Performing unnecessary WBC differentials adds to costs in the laboratory. Our objective was to implement a laboratory middleware algorithm to cancel repeat, same-day WBC differentials to achieve lasting improvements in laboratory resource allocation.

METHODS

Repeat same-day WBC differentials were first canceled only on intensive care unit samples; after a successful trial period, the algorithm was applied hospital-wide. We retrospectively reviewed CBC with differential orders from pre- and postimplementation periods to estimate the reduction in WBC differentials and potential cost savings.

RESULTS

The algorithm led to a monthly WBC differential cancellation rate of 5.40% for a total of 10,195 canceled WBC differentials during the cumulative postimplementation period (September 25, 2019, to December 31, 2020). Nearly all (99.94%) differentials remained canceled. Most patients only had one WBC differential canceled (range, 1-38). Savings estimates showed savings of $0.99 CAD per canceled differential and 1,060 minutes (17.7 hours) of technologist time.

CONCLUSIONS

A middleware algorithm to cancel repeat, same-day WBC differentials is a simple and sustainable way to achieve lasting improvements in laboratory utilization.

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

Digital morphology (DM) analyzers are widely applied in clinical practice. It is necessary to evaluate performances of DM analyzers by focusing on leukopenic samples. We evaluated the analytical performance, including precision, of a Sysmex DI-60 system (Sysmex, Kobe, Japan) on white blood cell (WBC) differentials in leukopenic samples. In a total of 40 peripheral blood smears divided into four groups according to WBC count (normal, mild, moderate, and severe leukopenia; each group n = 10), we evaluated precision of WBC preclassificaiton by DI-60. %coefficients of variation (%CVs) of precision varied for each sample and for each cell class; the fewer cells per slide, the higher %CV. The overall specificity and efficiency were high for all cell classes except plasma cells (95.9-99.9% and 90.0-99.4%, respectively). The largest absolute value of mean difference between DI-60 and manual count in each group was: 10.77, normal; 10.22, mild leukopenia; 19.09, moderate leukopenia; 47.74, severe leukopenia. This is the first study that evaluated the analytical performance of DI-60 on WBC differentials in leukopenic samples as the main subject. DI-60 showed significantly different performance depending on WBC count. DM analyzers should be evaluated separately in leukopenic samples, even if the overall performance was acceptable.

Educational cost-effective intervention to reduce pathologist's peripheral blood smears reviews with non-contributory findings: an academic institution experience

Peripheral blood smear (PBS) review by a pathologist is a necessary and invaluable diagnostic tool. However, innovative highly sophisticated haematology analysers that flag peripheral blood abnormalities have decreased the need for a PBS review. Ordering practices including PBS reviews lumped as part of an 'order set' or with complete blood count (CBC) constituted most PBS requests at our institution. A retrospective review of all PBS review orders from 1 April 2016 to 31 January 2017 was performed to investigate the ordering practices at our institution. A total of 2864 PBS were ordered during the above study period. In many cases, the PBS report did not add any significant clinical information beyond that acquired by the CBC and differential count. These findings inspired policy changes within our institution for pathologist PBS reviews. Within the electronic order system, all PBS orders for inpatients were linked to a pop-up window with criteria for peripheral smear review and instructions on the approval policy. Outpatient orders required clinicians to request pathology approval. This implementation reduced total number of PBS orders by 42.5% with no adverse effect on patient management. Empowering pathologists and clinicians with guidelines on PBS review orders is a beneficial educational exercise of resource utilisation. Discussion with physicians regarding clinical indications reduces non-contributory PBS reviews, provides guidance to appropriate testing, and aptly allocates pathologist and laboratory staff time and resources.

Evaluation of Scopio Labs X100 Full Field PBS: The first high-resolution full field viewing of peripheral blood specimens combined with artificial intelligence-based morphological analysis

Background

Current digital cell imaging systems perform peripheral blood smear (PBS) analysis in limited regions of the PBS and require the support of manual microscopy without achieving full digital microscopy. We report a multicenter study that validated the Scopio Labs X100 Full Field PBS, a novel digital imaging system that utilizes a full field view approach for cell recognition and classification, in a decision support system mode.

Methods

We analyzed 335 normal and 310 abnormal PBS from patients with various clinical conditions and compared the performance of Scopio's Full Field PBS as the test method, with manual PBS analysis as the reference method. Deming regression analysis was utilized for comparisons of WBC and platelet estimates. Measurements of WBC and platelet estimation accuracy along with the agreement on RBC morphology evaluation were performed. Reproducibility and repeatability (R&R) of the system were also evaluated.

Results

Scopio's Full Field PBS WBC accuracy was evaluated with an efficiency of 96.29%, sensitivity of 87.86%, and specificity of 97.62%. The agreement between the test and reference method for RBC morphology reached 99.77%, and the accuracy for platelet estimation resulted in an efficiency of 94.89%, sensitivity of 90.00%, and specificity of 96.28%, with successful R&R tests. The system enabled a comprehensive review of full field PBS as shown in representative samples.

Conclusions

Scopio's Full Field PBS showed a high degree of correlation of all tested parameters with manual microscopy. The novel full field view of specimens facilitates the long‐expected disengagement between the digital application and the manual microscope.

High-Efficiency Classification of White Blood Cells Based on Object Detection

White blood cells (WBCs) play a significant role in the human immune system, and the content of various subtypes of WBCs is usually maintained within a certain range in the human body, while deviant levels are important warning signs for diseases. Hence, the detection and classification of WBCs is an essential diagnostic technique. However, traditional WBC classification technologies based on image processing usually need to segment the collected target cell images from the background. This preprocessing operation not only increases the workload but also heavily affects the classification quality and efficiency. Therefore, we proposed one high-efficiency object detection technology that combines the segmentation and recognition of targets into one step to realize the detection and classification of WBCs in an image at the same time. Two state-of-the-art object detection models, Faster RCNN and Yolov4, were employed and comparatively studied to classify neutrophils, eosinophils, monocytes, and lymphocytes on a balanced and enhanced Blood Cell Count Dataset (BCCD). Our experimental results showed that the Faster RCNN and Yolov4 based deep transfer learning models achieved classification accuracy rates of 96.25% and 95.75%, respectively. For the one-stage model, Yolov4, while ensuring more than 95% accuracy, its detection speed could reach 60 FPS, which showed better performance compared with the two-stage model, Faster RCNN. The high-efficiency object detection network that does not require cell presegmentation can remove the difficulty of image preprocessing and greatly improve the efficiency of the entire classification task, which provides a potential solution for future real-time point-of-care diagnostic systems.

Brightfield and fluorescence in-channel staining of thin blood smears generated in a pumpless microfluidic

Effective staining of peripheral blood smears by increasing contrast of intracellular components and biomarkers is essential for the accurate characterization, diagnosis, and monitoring of various diseases such as malaria. To assess the potential for automation of stained whole human blood smears at the point-of-care (POC), brightfield and fluorescence staining protocols were adapted for smears generated in channels of pumpless microchannels and compared to a standard glass smear. A 3× concentration Giemsa brightfield staining solutions (10, 33, and 50% dilution), and Acridine Orange fluorescence staining solutions (12 μg mL-1) were evaluated with human blood smears containing malaria parasites within a microfluidic channel. Giemsa staining at 33% dilution showed an optimal combination of contrast and preservation of cellular morphology, while 50% dilutions showed significant cellular crenation and 10% dilutions did not show desired contrast in brightfield imaging. Fluorescence staining at 12 μg mL-1 using Acridine Orange showed clear separability between the fluorescent intensities of the malaria parasites and that of the red blood cells (RBCs) and background. However, compared to glass smears, these exhibited reduced signal intensity as well as inverted contrast of RBCs and background. These results demonstrate that peripheral thin blood smears generated in pumpless microfluidic can be successfully stained in-channel with a simple, one-step procedure to permit brightfield and fluorescence imaging.

Smudge Cells in Chronic Lymphocytic Leukemia: Pathophysiology, Laboratory Considerations, and Clinical Significance

Chronic lymphocytic leukemia (CLL) is the most commonly encountered leukemia in the clinical laboratory. Cytoskeletal defects in CLL lymphocytes can result in the formation of up to 75% smudge cells (SCs) during blood film preparation. Failure to account for these damaged lymphocytes in the white blood cell (WBC) differential diminishes the accuracy and reproducibility of the results. Lacking clear practice standards on handling SCs in CLL, different laboratories may employ different methods to mitigate SC-induced errors. This review explores the pathophysiology of SCs, their effect on WBC differentials in CLL, and how these results can impact clinical decisions. The pros and cons of various SC corrective methods are described to assist laboratories in developing an optimized protocol to reduce errors and inconsistencies in WBC differentials. Finally, the potential utility of SC enumeration as an indicator of CLL prognosis is discussed in terms of laboratories with differing access to technology.

Effects of Image Quantity and Image Source Variation on Machine Learning Histology Differential Diagnosis Models

Aims

Histology, the microscopic study of normal tissues, is a crucial element of most medical curricula. Learning tools focused on histology are very important to learners who seek diagnostic competency within this important diagnostic arena. Recent developments in machine learning (ML) suggest that certain ML tools may be able to benefit this histology learning platform. Here, we aim to explore how one such tool based on a convolutional neural network, can be used to build a generalizable multi-classification model capable of classifying microscopic images of human tissue samples with the ultimate goal of providing a differential diagnosis (a list of look-alikes) for each entity.

Methods

We obtained three institutional training datasets and one generalizability test dataset, each containing images of histologic tissues in 38 categories. Models were trained on data from single institutions, low quantity combinations of multiple institutions, and high quantity combinations of multiple institutions. Models were tested against withheld validation data, external institutional data, and generalizability test images obtained from Google image search. Performance was measured with macro and micro accuracy, sensitivity, specificity, and f1-score.

Results

In this study, we were able to show that such a model's generalizability is dependent on both the training data source variety and the total number of training images used. Models which were trained on 760 images from only a single institution performed well on withheld internal data but poorly on external data (lower generalizability). Increasing data source diversity improved generalizability, even when decreasing data quantity: models trained on 684 images, but from three sources improved generalization accuracy between 4.05% and 18.59%. Maintaining this diversity and increasing the quantity of training images to 2280 further improved generalization accuracy between 16.51% and 32.79%.

Conclusions

This pilot study highlights the significance of data diversity within such studies. As expected, optimal models are those that incorporate both diversity and quantity into their platforms.s.

Deep-Learning Based Label-Free Classification of Activated and Inactivated Neutrophils for Rapid Immune State Monitoring

The differential count of white blood cells (WBCs) is one widely used approach to assess the status of a patient’s immune system. Currently, the main methods of differential WBC counting are manual counting and automatic instrument analysis with labeling preprocessing. But these two methods are complicated to operate and may interfere with the physiological states of cells. Therefore, we propose a deep learning-based method to perform label-free classification of three types of WBCs based on their morphologies to judge the activated or inactivated neutrophils. Over 90% accuracy was finally achieved by a pre-trained fine-tuning Resnet-50 network. This deep learning-based method for label-free WBC classification can tackle the problem of complex instrumental operation and interference of fluorescent labeling to the physiological states of the cells, which is promising for future point-of-care applications.

Establishment of improved review criteria for hematology analyzers in cancer hospitals

BACKGROUND

Although hematologic review criteria for general hospitals have been established, they may be insufficient for cancer hospitals. This study aimed to establish the appropriate review criteria for hematology analyzers in cancer hospitals.

METHODS

A total of 1003 samples from our hospital were randomly selected for blood smear preparation and microscopic review. The review criteria of the International Consensus Group for Hematology Review (ICGH) and Chinese consensus group were used to obtain the review, true-negative (TN), true-positive (TP), false-negative (FN), and false-positive (FP) rates, as well as the triggered rules. Our review criteria were established by comparing flag or numeric value information of TP and FP samples, adjusting rules to obtain better efficiency, a low slide review rate, and an acceptable FN rate.

RESULTS

Overall, 197 (19.64%) samples showed positive smear findings. Compared to the ICGH criteria, the slide review rate of the newly established criteria declined from 51.25% to 39.28%, and the TP and TN rates increased from 17.85% and 46.06% to 23.13% and 55.83%, respectively. The FN rate of the newly established criteria was 3.69%. Another set of samples used to validate the newly established criteria yielded the review, FN, and FP rates as 33.49%, 1.86%, and 25.58%, respectively.

CONCLUSION

The newly established review criteria for hematology analyzers enabled the prompt identification, smear, and further verification of doubtful specimens, without a significant increase in the workload, thus improving the efficiency of the review process. This study provided data support for other cancer hospitals to establish review criteria.

Clinician-ordered peripheral blood smears have low reimbursement and variable clinical value: a three-institution study, with suggestions for operational efficiency

Background

Peripheral blood smears are performed to evaluate a variety of hematologic and non-hematologic disorders. At the authors’ institutions, clinician requests for pathologist-performed blood smear reviews have increased in recent years. Blood smears may contribute significantly to pathologists’ workloads, yet their clinical value is variable, and professional reimbursement rates are low. This study aimed to identify clinical scenarios in which smear review is likely to provide value beyond automated laboratory testing.

Methods

Blood smear review practices at three institutions were examined, and the indications for and interpretations of clinician-initiated smears were reviewed to determine the percentage of smears with potential added clinical value. A smear review was classified as having added clinical value if the pathologist’s interpretation included a morphologic abnormality that had the potential to impact patient management, and that could not be diagnosed by automated complete blood count with white blood cell differential or automated iron studies alone.

Results

Among 515 consecutive clinician-requested smears performed during the study timeframes, 23% yielded interpretations with potential added clinical value. When sorted by indication, 25, 19, and 13% of smear reviews requested for white blood cell abnormalities, red blood cell abnormalities, and platelet abnormalities, respectively, had findings with potential added clinical value. The proportion of smears with potential clinical value differed significantly across these three categories (p = 0.0375).

Conclusions

Smear review ordering practices across three institutions resulted in a minority of smears with potential added clinical value. The likelihood of value varied according to the indication for which the smear was requested. Given this, efforts to improve the utilization and efficiency of smear review are worthwhile. Solutions are discussed, including engaging laboratory staff, educating clinicians, and modifying technology systems.

Laboratory practices for manual blood film review: Results of an IQMH patterns of practice survey

INTRODUCTION

Examination of a blood film is the second most common hematology test, after the complete blood count. Interpretation of a peripheral blood film by trained laboratory professionals provides valuable diagnostic information. The Institute for Quality Management in Healthcare (IQMH) Hematology Scientific Committee developed a questionnaire to gather information regarding current practices for manual blood film review and reporting from laboratories participating in IQMH Morphology proficiency testing (PT) surveys.

METHODS

An online survey was distributed to 174 laboratories, 97% submitted results.

RESULTS

Of the respondents, the majority (82%) indicated affiliation with small- or medium-sized hospitals (<500 beds). 80% of respondents had core laboratory technologists performing manual blood film reviews, while only 2% utilized dedicated hematology technologists with morphology expertise. All respondents had a policy for manual blood film review by a technologist, 70% did not have blood films reviewed by a senior/charge technologist prior to review by a physician. The majority (88%) of participants included morphological findings in their critical result list; of these, 98% include malaria and 88% include the first-time finding of blasts as critical results. 59% of participants indicated that they have a procedure in place to ensure that interpretation and confirmation of first-time potentially significant morphological findings are available from a physician at all times.

CONCLUSION

This survey identified significant variation in blood film review and reporting practices across participating laboratories. The IQMH Hematology Scientific Committee will develop best practice recommendations to guide and standardize practice.

Multicentric evaluation of analytical performances digital morphology with respect to the reference methods by manual optical microscopy

AIMS

Optical microscopic (OM) evaluation of peripheral blood (PB) cells is still a crucial step of the laboratory haematological workflow. The morphological cell analysis is time-consuming and expensive and it requires skilled operator. To address these challenges, automated image-processing systems, as digital morphology (DM), were developed in the last few years. The aim of this multicentre study, performed according to international guidelines, is to verify the analytical performance of DM compared with manual OM, the reference method.

METHODS

Four hundred and ninety PB samples were evaluated. For each sample, two May Grunwald-stained and Giemsa-stained smears were performed and the morphological evaluation of cells was analysed with both DM and OM. In addition, the assessment times of both methods were recorded.

RESULTS

Comparison of DM versus OM methods was assessed with Passing-Bablok and Deming fit regression analysis: slopes ranged between 0.17 for atypical, reactive lymphocytes and plasma cells (LY(AT)) and 1.24 for basophils, and the intercepts ranged between -0.09 for blasts and 0.40 for LY(AT). The Bland-Altman bias ranged between -6.5% for eosinophils and 21.8% for meta-myemielocytes. The diagnostic agreement between the two methods was 0.98. The mean of assessment times were 150 s and 250 s for DM and OM, respectively.

CONCLUSION

DM shows excellent performance. Approximately only 1.6% of PB smears need the OM revision, giving advantages in terms of efficiency, standardisation and assessment time of morphological analysis of the cells. The findings of this study may provide useful information regarding the use of DM to improve the haematological workflow.

Estimation of white blood cell and platelet counts in ovine blood smears, and a comparison with the ADVIA 120 hematology analyzer

BACKGROUND

Manual evaluation of blood cell counts on stained blood films is a common procedure in resource-limited laboratories of farm animal clinics. Moreover, settings for sheep blood cell counts are not provided on most veterinary hematology analyzers.

OBJECTIVES

We aimed to (a) compare the results of white blood cell (WBC) counts evaluated microscopically on ovine blood smears with those obtained by the ADVIA 120 hematology analyzer and validate appropriate correction factors for the manual technique; and (b) assess the two suggested factors to calculate platelet counts on blood smears in sheep.

METHODS

The blood samples of 57 sheep were used to generate a regression equation between the average WBC count per field and the WBC count determined using the ADVIA 120 analyzer. Thirty-one new ovine samples were used to assess the agreement between the calculated WBC counts based on a generated equation and those obtained by the analyzer using the Passing-Bablok test and Bland-Altman plots. Similarly, agreements between platelet counts using two different factors for platelet calculation were assessed using the Bland-Altman plot.

RESULTS

The average bias of calculated WBC counts was 0.4%, with precision and accuracy being over 95%. Regarding calculated platelet counts, Bland-Altman plots revealed a bias of 26.4% and 1.4% when the average number of platelets per field was multiplied by 15 000 and 20 000, respectively.

CONCLUSIONS

Microscopic WBC counting in ovine blood is a reliable alternative to automated analyses using the generated equation. A better agreement between the two methods was observed when a factor of 20 000 was used to calculate platelet counts in ovine blood smears.

Rapid drug detection in whole blood droplets using a desorption electrospray ionization static profiling approach - a proof-of-concept

RATIONALE

The introduction of desorption electrospray ionization (DESI) - and ambient desorption/ionization (ADI) ion sources in general - in the 2000s has opened new possibilities for mass spectrometric (MS) analyses of biological sample surfaces. DESI allows for a rapid screening of solid samples because no sample preparation is needed and the analysis is performed at atmospheric pressure. In the present study, we used DESI as an ion source for the rapid detection of a small molecule in blood droplets deposited on glass slides.

METHODS

Blood was spiked with different concentrations of a model drug, mebendazole. One microliter blood droplets of each preparation were deposited on the surface of a glass slide and analyzed by DESI, either in imaging or profiling mode.

RESULTS

The results suggested that DESI imaging mode was not appropriate for the detection of mebendazole in blood droplets as an initial solvation time was necessary before the obtention of signal. A profiling approach consisting of analyzing a single position of the blood droplet was used for further analysis and allowed mebendazole to be detected in the fg range and to monitor the volume of sample analyzed.

CONCLUSIONS

The study suggests that profiling mode at a single position is adequate for DESI analyses in whole blood droplets. This proof-of-concept study illustrates the potential of DESI profiling as a possible alternative to liquid chromatography/MS analyses of whole blood, when analyses are needed within a restricted time. Rapid detection methods in blood at atmospheric pressure may find interesting applications in the fields of toxicology and pharmacology.

Intra- and inter-rater agreement for the detection of band neutrophils and toxic change in horses

BACKGROUND

The detection of band neutrophils and toxic change via microscopic blood smear review is vitally important, as their presence indicates systemic inflammation. However, in-clinic evaluation of WBC morphology is often limited.

OBJECTIVE

We aimed to determine the agreement between expert raters in the detection of bands and toxic change.

METHODS

Three board-certified clinical pathologists each evaluated 109 blood smears from horses with acute disease, and 19 control smears from healthy horses. The pathologists determined if bands were present, and if so, the percentage of bands present. They also determined if toxic change was present, and if so, the grade of toxic change. Intra-rater agreement was evaluated using 12 duplicate blood smears. Agreement on the presence of bands between pathologists and an in-clinic hematology analyzer was evaluated.

RESULTS

Intra-rater agreement was substantial to almost perfect. Agreement between pathologists for the detection of bands was moderate, but when pathologists agreed bands were present, there was excellent agreement on the percentage of bands and mature neutrophils. Agreement between pathologists for the detection of high-grade, clinically relevant toxic change was fair. When pathologists agreed high-grade toxic change was present, there was fair agreement on Döhle bodies and cytoplasmic basophilia and poor agreement on cytoplasmic vacuolation. Agreement between individual pathologists and the in-clinic hematology analyzer for the indication of bands was fair to moderate.

CONCLUSIONS

Consistent identification of bands and toxic change is challenging, even for highly trained personnel. It is, thus,not surprising that in-clinic blood smear evaluation of WBC morphology by non-experts could be inadequate.

Periodontal Disease Impairs Muscle Recovery by Modulating the Recruitment of Leukocytes

The purpose of this study is to analyze the impact of periodontal disease (PD) associated with physical exercise on inflammatory mediators and muscle repair. Twenty-four Wistar rats were divided into four groups: control (SH), healthy trained (TH), sedentary with PD (SP), and trained with PD (TP). PD was induced in groups SP and TP while the trained groups performed treadmill exercises for 8 weeks. For the analysis of IL-6, IL-10, TNF-α, and leukocyte count, we collected blood samples. Cryolesions were induced in the tibialis anterior and gastrocnemius, which were analyzed for morphological changes. The presence of PD modified leukocyte counts, while exercise showed an additive role. PD increased levels of IL-6, IL-10, and TNF-α, and physical exercise changed only values of IL-10. The association between physical exercise and PD was responsible for an increased concentration of leukocytes in the region of the inflammation. Serum levels of inflammatory markers were modified by PD and, when combined with exercise, may negatively modulate inflammation. The association between PD and physical exercise showed the most significant changes in the number of inflammatory cells and may negatively influence the process of muscle repair.

Preliminary evaluation of a new flow cytometry method for the routine hematology workflow

Background In a generalist laboratory, the integration of the data obtained from hematology analyzers (HAs) with those from multiparametric flow cytometry (FMC) could increase the specificity and sensitivity of first level screening to identify the pathological samples. The aim of this study was to perform a preliminary evaluation of a new simple hybrid method (HM). The method was obtained by integration between HAs reagents into FCM, with a basic monoclonal antibodies panel for the leukocytes differential count. Methods Eighty-one peripheral blood samples, collected in K3EDTA tubes, were analyzed by XN-module, and CyFlow Space System, using both standard MoAbs and HM method analysis, and with the optical microscopy (OM). Within-run imprecision was carried out using normal samples, the carryover was evaluated, data comparison was performed with Passing-Bablok regression and Bland-Altman plots. Results The within-run imprecision of HM methods ranged between 1.4% for neutrophils (NE) and 10.1% for monocytes (MO) always equal or lower to the OM. The comparison between HM methods vs. OM shows Passing-Bablok regression slopes comprised between 0.83 for lymphocyte (LY) and 1.14 for MO, whilst the intercepts ranged between -0.18 for NE and 0.25 for LY. Bland-Altman relative bias was comprised between -12.43% for NE, and 19.77% for eosinophils. In all 11 pathological samples the agreement between the methods was 100%. Conclusions The new hybrid method generates a leukocytes differential count suitable for routine clinical use and it is also useful for identifying morphological abnormalities with a reduction in cost and improvement of screening for first level hematology workflow.

Optimization of Laboratory Ordering Practices for Complete Blood Count With Differential

Objectives

To investigate the utilization of CBC and CBC with differential (CBC w/diff) tests at University of Alabama at Birmingham Hospital, and to determine if a reduction in CBC w/diff tests could be achieved without negatively impacting patient care.

Methods

The quantity of testing and distribution of repeated tests before, during, and after an educational intervention were compared.

Results

CBC w/diff tests were ordered 10-fold more frequently than CBC tests. The trauma burn intensive care unit ordered the most CBC w/diff tests, with repeat tests done every 4 or 12 hours. The educational intervention reduced the number of CBC w/diff tests ordered and tests repeated every 12 hours.

Conclusions

The educational intervention changed the ordering practices of CBC w/diff and CBC tests. This was sustained after the intervention and no negative effects on patient care were noted. Similar interventions may lead to optimization of ordering practices of other laboratory tests.

Normal values of neutrophil-to-lymphocyte ratio, lymphocyte-to-monocyte ratio and platelet-to-lymphocyte ratio among Iranian population: Results of Tabari cohort

BACKGROUND

Neutrophil-lymphocyte ratio (NLR), lymphocyte-monocyte ratio (LMR) and platelet-lymphocyte ratio (PLR) have a prognostic value in several types of diseases such as cancers and they vary in different races. So, we aimed to evaluate the normal range of these markers among healthy people to determine the normal value in Iranian population.

METHODS

In the present study, cross-sectional data of population-based cohort study named "Tabari cohort study" was utilized. In the first phase of Tabari cohort, 10255 participants aged 35-70 years from urban and rural areas of Sari, Mazandaran, Iran entered into the study. The study included a questionnaire survey and blood collection. Blood samples were collected after 12 hours fasting from all participants during the study. Hematological indices were measured for all samples using Celltac Alpha MEK-6510 K (Tokyo, Japan).

RESULTS

After sample exclusion, 2212 healthy subjects of Tabari's normal cohort population were investigated. The mean age of the samples was 47.9±9.29 years. The mean of NLR, LMR, PLR were 1.70±0.70, 11.15±3.14 and 117.05±47.73, respectively.

CONCLUSION

Our investigation provides preliminary reference values for NLR, LMR, and PMR among Iranian population that can be used for disease progress in various clinical procedures.