Leukocyte cell population analysis from the coulter automatic blood cell analyzer DxH800 to monitor the effect of G-CSF

Research use only and cell population data items obtained from the Beckman Coulter DxH800 automated hematology analyzer are useful in discriminating MDS patients from those with cytopenia without MDS

We investigated the performance of research use only/cell population data (RUO/CPD) items obtained from the Beckman Coulter DxH800 automated hematologic analyzer in discriminating MDS patients from cytopenic patients without MDS.Total of 14 routine CBC, 18 research use only (RUO) items, and 70 CPD items were obtained retrospectively at diagnosis. The results were then compared between 94 MDS patients and 100 cytopenic patients without MDS. In items with statistically significant differences, receiver operating characteristic (ROC) analysis was performed and the results were compared.Four CBC/RUO items [red cell distribution width-standard deviation (RDW-SD), immature reticulocyte fraction (IRF), mean sphered cell volume (MSCV), high light scatter reticulocytes (HLR)], and two CPD items [mean volume of neutrophils (NE-V-Mean) and mean volume of early granulated cells (EGC-V-Mean)] showed area-under the curve (AUC) scores > 0.750. Notably, four RUO/CPD items (MSCV > 81.4/HLR > 0.15%/NE-V-Mean > 145/EGC-V-Mean > 156) showed high sensitivity (91.9%/93.6%/88.1%/90.2%, respectively) in discriminating MDS patients from cytopenic patients without MDS. With these six items, scores ≥ 4 (defined as ≥ 4 items exceeding cutoff values out of six items) showed AUC scores/sensitivity/specificity/accuracy (0.891/87.3%/79.0%/83.0%, respectively).Six CBC/RUO/CPD items showed satisfactory AUC scores of > 0.750, and four RUO/CPD items showed high sensitivity in discriminating MDS patients from cytopenic patients without MDS. Scoring system with six items showed high sensitivity, specificity, and accuracy with decision criteria of ≥ 4 scores. Therefore, DxH800 RUO/CPD items would be useful in discriminating MDS patients from cytopenic patients without MDS.

Beyond the In-Practice CBC: The Research CBC Parameters-Driven Machine Learning Predictive Modeling for Early Differentiation among Leukemias

A targeted and timely treatment can be a beneficial tool for patients with hematological emergencies (particularly acute leukemias). The key challenges in the early diagnosis of leukemias and related hematological disorders are their symptom-sharing nature and prolonged turnaround time as well as the expertise needed in reporting confirmatory tests. The present study made use of the potential morphological and immature fraction-related parameters (research items or cell population data) generated during complete blood cell count (CBC), through artificial intelligence (AI)/machine learning (ML) predictive modeling for early (at the pre-microscopic level) differentiation of various types of leukemias: acute from chronic as well as myeloid from lymphoid. The routine CBC parameters along with research CBC items from a hematology analyzer in the diagnosis of 1577 study subjects with hematological neoplasms were collected. The statistical and data visualization tools, including heat-map and principal component analysis (PCA,) helped in the evaluation of the predictive capacity of research CBC items. Next, research CBC parameter-driven artificial neural network (ANN) predictive modeling was developed to use the hidden trend (disease’s signature) by increasing the auguring accuracy of these potential morphometric parameters in differentiation of leukemias. The classical statistics for routine and research CBC parameters showed that as a whole, all study items are significantly deviated among various types of leukemias (study groups). The CPD parameter-driven heat-map gave clustering (separation) of myeloid from lymphoid leukemias, followed by the segregation (nodding) of the acute from the chronic class of that particular lineage. Furthermore, acute promyelocytic leukemia (APML) was also well individuated from other types of acute myeloid leukemia (AML). The PCA plot guided by research CBC items at notable variance vindicated the aforementioned findings of the CPD-driven heat-map. Through training of ANN predictive modeling, the CPD parameters successfully differentiate the chronic myeloid leukemia (CML), AML, APML, acute lymphoid leukemia (ALL), chronic lymphoid leukemia (CLL), and other related hematological neoplasms with AUC values of 0.937, 0.905, 0.805, 0.829, 0.870, and 0.789, respectively, at an agreeably significant (10.6%) false prediction rate. Overall practical results of using our ANN model were found quite satisfactory with values of 83.1% and 89.4.7% for training and testing datasets, respectively. We proposed that research CBC parameters could potentially be used for early differentiation of leukemias in the hematology–oncology unit. The CPD-driven ANN modeling is a novel practice that substantially strengthens the predictive potential of CPD items, allowing the clinicians to be confident about the typical trend of the “disease fingerprint” shown by these automated potential morphometric items.

Diagnostic and prognostic utility of WBC counts and cell population data in patients with COVID-19

Introduction

Early diagnosis and identification of potential critical cases for timely treatment are crucial for COVID‐19 patients. The aim of this study was to analyze the diagnostic and prognostic implications of WBC and cell population data (CPD) abnormalities related to COVID‐19 at disease onset.

Methods

Baseline WBC counts and CPD data were analyzed in one hundred COVID‐19 patients presenting to emergency department and subsequently discharged (n=49), admitted (n=51) or deceased (n=22), and in 47 healthy subjects.

Results

Lymphopenia and eosinopenia were observed in all COVID‐19 patients, with more intensity in the admitted and deceased groups, that also presented increased WBC and neutrophil counts. On CPD analysis, COVID‐19 was associated with increased volume of neutrophils, lymphocytes, and monocytes, whereas conductivity was decreased for neutrophils and increased for lymphocytes. The ROC curve analysis showed good performance for lymphocyte counts in predicting COVID‐19 diagnosis (AUC=0.858), for neutrophil counts in predicting admission for COVID‐19 (AUC=0.744) and for monocytes volume in predicting COVID‐19 diagnosis (AUC=0.837).

Conclusion

WBC counts and CPD parameters at disease onset in COVID‐19 patients can improve diagnostic characterization and aid in the discrimination between severe and nonsevere presentations.

Discriminating myelodysplastic syndrome and other myeloid malignancies from non-clonal disorders by multiparametric analysis of automated cell data

BACKGROUND

We investigated the usefulness of novel complete blood count (CBC) data for discriminating myeloid malignancies from non-clonal CBC abnormalities.

METHODS

Data were obtained during routine CBC tests of 119 samples from 37 myelodysplastic syndrome (MDS) patients, 92 samples from 45 myeloproliferative neoplasm (MPN) patients, and 15 samples from 11 chronic myelogenous leukemia (CML) patients using a DxH800 (Beckman Coulter). Data obtained from patients with hypocellular bone marrow and from those with other non-clonal diseases with CBC abnormalities were included in the comparisons.

RESULTS

For cell population data of neutrophils, the means of median, upper median, lower median, and low angle light scatters were significantly lower in MDS patients than in patients without hematological malignancies. Low hemoglobin density (LHD) did not significantly differ between the MDS and non-clonal cytopenia patients, but it was significantly higher in the MPN and CML patients. We selected 13 parameters and scored the MDS diagnosis using cut-off values obtained from receiver operating characteristic (ROC) curve analysis. Using a score > 9, MDS was distinguished from non-clonal cytopenia with a sensitivity of 92.4% and a specificity of 85.4%.

CONCLUSIONS

Multiparametric analyses of new automated parameters are useful for discriminating MDS from non-clonal cytopenia.

Identification of cell morphology parameters from automatic hematology analyzers to predict the peripheral blood CD34-positive cell count after mobilization

Optimal timing of apheresis initiation is important for maximizing the hematopoietic stem cell (HSC) yield. This study aimed to identify useful parameters from automatic hematology analyzers for predicting the peripheral blood CD34+ cell count after mobilization. We prospectively enrolled 53 healthy donors and 72 patients, and evaluated 43 cell morphology parameters from Unicel DxH800 (Beckman Coulter, USA) and Advia 2120i (Siemens Healthcare Diagnostics, USA). The correlation of each parameter with the CD34+ cell count in pre-apheresis blood samples was analyzed. The delta neutrophil index (DNI) from Advia 2120i, standard deviation of volume of neutrophils and monocytes (SD-V-NE and SD-V-MO), standard deviation of conductivity of neutrophils and monocytes (SD-C-NE and SD-C-MO), mean conductivity of neutrophils and monocytes (MN-C-NE and MN-C-MO), and standard deviation of axial light loss of neutrophils and monocytes (SD-AL2-NE and SD-AL2-MO) from DxH800 showed significant correlations with the CD34+ cell count. SD-V-NE, SD-C-NE, and SD-C-MO showed good or fair area under the curve values for the prediction of the CD34+ cell count. SD-V-NE, SD-C-NE, and SD-C-MO from DxH800 will provide rapid, useful information for the initiation of apheresis after mobilization.

Cell population data in neonates: differences by age group and associations with perinatal factors

INTRODUCTION

Cell population data (CPD) describe physical parameters of white blood cell subpopulations and are reported to be of some value in the diagnosis of sepsis in neonates. Before using the CPD for diagnosing sepsis, the baseline features of the CPD distribution in healthy neonates should be clarified. The aim of this study was to compare the CPD distributions of healthy neonates and other age groups and to identify perinatal factors that are associated with changes in the CPD distribution of healthy neonates.

METHODS

The CPD distribution of 69 samples from term neonates was compared with adolescents and adults. The CPD distribution of 163 samples from healthy neonates was analyzed in association with perinatal factors, including gestational age, chronologic age, birthweight, delivery mode, premature rupture of membranes, diabetes, and pregnancy-induced hypertension.

RESULTS

The CPD distribution for term neonates was significantly different from those in adolescents and adults. The mean lymphocyte volume showed a negative correlation with gestational age at birth (r = -0.305; P < 0.01). The mean neutrophil volume was smaller in the cesarean section group than in the normal delivery group. The small for gestational age (SGA) group had smaller mean neutrophil volume and mean monocyte volume than the appropriate for gestational age group.

CONCLUSION

The CPD distribution of healthy neonates differed from those of adolescents or adults, and the differences were associated with gestational age, delivery mode, and being SGA.

Automated screening for tuberculosis by multiparametric analysis of data obtained during routine complete blood count

INTRODUCTION

The main goal of this study was to develop a multiparametric cell population data (CPD) model that combines information from several morphologic parameters generated by DxH800, in addition to the traditional parameters regularly reported in the CBC-diff, and to test the performance of this model in screening the general population for primary tuberculosis (TB).

METHODS

A total of 3741 study cases were divided into two groups, test and validation set at cut-off value of 6000 WBCs/μL. We developed multiparametric model for primary TB screening (TB hemeprint), selected CPD, and calculated parameters which could discriminate primary TB from other non-TB diseases and normal control in test set. We applied it to the validation set, which was a set of completely different samples, to test its reproducibility if applied to a routine laboratory test.

RESULTS

After screening primary TB using TB hemeprint, sensitivity, specificity, PPV, and NPV were 85.4%, 89.6%, 31.1%, and 99.1%, respectively, in primary TB with lower than 6000 WBCs/μL of test set (test set-L). In primary TB with higher than 6000 WBCs/μL of test set (test set-H), those values were 83.1%, 85.6%, 29.7%, and 98.6%, respectively. There were only 0.4% (2/461) and 0.6% (2/326) of normal control samples included in test set-L and -H, respectively. Diagnostic efficiencies except sensitivity in each validation set were very comparable with those in each test set.

CONCLUSION

Tuberculosis hemeprint may allow us to screen primary TB with acceptable sensitivity and specificity using combination of TB-specific CPD and calculated parameters.

Leukocyte cell population data (volume conductivity scatter) in postprandial leukocyte activation

INTRODUCTION

Changes in leukocyte cell population data have been reported in various infectious diseases, but little is known in other inflammatory conditions such as the postprandial state. We investigated whether leukocyte cell population data change during postprandial leukocyte activation.

METHODS

Healthy volunteers underwent a standardized oral fat loading test (OFLT). Flowcytometric quantitation of leukocyte activation markers CD11b, CD66b, CD35, and CD36, together with leukocyte cell population data from LH750 hematology analyzers were measured fasting and at 4 and 8 h postprandially.

RESULTS

Twelve volunteers were included. Postprandial leukocyte activation was confirmed by increased expression of CD11b by monocytes (+11.7%) and neutrophils (+15.0%) and by increased expression of CD66b (+14.7%) and CD35 (+16.6%) by neutrophils at T = 4 h. The mean scatter from neutrophils, reflecting granularity, significantly decreased at T = 4 h (P < 0.05) and returned to baseline at T = 8 h (P-anova 0.048). The mean volume of monocytes increased significantly at T = 4 h (P < 0.001) and returned to baseline at T = 8 h (P-anova 0.0008). At T = 4 h, CD11b expression on neutrophils was associated with a reduction in mean scatter of neutrophils (Pearson's r: -0.677, P = 0.016).

CONCLUSION

Postprandial leukocyte activation is accompanied by temporary changes in leukocyte cell population data, similar to changes observed during various infections, but to a lesser extent.