Development and validation of an app-based cell counter for use in the clinical laboratory setting

Development and Pilot Testing of a Comprehensive Mobile Application to Assist Cell Count Determination During Peripheral Smear and Bone Marrow Examination

BACKGROUND

In the modern era of complete blood count analysis, manual differential count is performed whenever 'flags' are generated by an automated hematology analyzer. Traditionally, tally counters with five or eight keys are used for manual differential count. A few mobile applications are available to perform this task; however, the application features and cell representation are limited.

OBJECTIVES

The primary objective of our study was to develop an indigenous, comprehensive mobile application to assist with manual blood cell differential count. The secondary objective was to measure the usability of a newly developed application among undergraduate medical students.

MATERIALS AND METHODS

A new mobile application was developed using a Java development kit, Version 11.0.13 (Oracle Corporation, Austin, USA) in Android Studio Dolphin (2021.3.1) (Google, California, USA). The application content was validated by three pathologists with more than five years of experience. The app's usability was tested among 60 participants using a validated mHealth App Usability Questionnaire (MAUQ). The questionnaire had 18 items covering three domains: ease of use, interface & satisfaction, and usefulness.

RESULTS

The newly developed application supports peripheral smear WBC differential count, platelet count, reticulocyte count, malaria parasite quantification, and bone marrow differential count. During usability testing, the app was easy to use in 95% (57/60) of participants, time-efficient in 91.7% (55/60), and helpful for healthcare practice learning in 96.7% (58/60). The total mean score was 6.11, indicating high usability.

CONCLUSION

A comprehensive mobile application to assist manual differential count with adequate cell representation was developed. The mobile application was easy to use, time-efficient, and valuable among the study participants.

N-thiocarboxyanhydrides, amino acid-derived enzyme-activated H2S donors, enhance sperm mitochondrial activity in presence and absence of oxidative stress

BACKGROUND

Hydrogen sulfide (H₂S) donors are crucial tools not only for understanding the role of H₂S in cellular function but also as promising therapeutic agents for oxidative stress-related diseases. This study aimed to explore the effect of amino acid-derived N-thiocarboxyanhydrides (NTAs), which release physiological H₂S levels in the presence of carbonic anhydrase, on porcine sperm function during short-term incubation with and without induced oxidative stress. For this purpose, we employed two H₂S-releasing NTAs with release half-lives (t_1/2) in the range of hours that derived from the amino acids glycine (Gly-NTA) or leucine (Leu-NTA). Because carbonic anhydrase is crucial for H₂S release from NTAs, we first measured the activity of this enzyme in the porcine ejaculate. Then, we tested the effect of Gly- and Leu-NTAs at 10 and 1 nM on sperm mitochondrial activity, plasma membrane integrity, acrosomal status, motility, motile subpopulations, and redox balance during short-term incubation at 38 °C with and without a reactive oxygen species (ROS)-generating system.

RESULTS

Our results show that carbonic anhydrase is found both in spermatozoa and seminal plasma, with activity notably higher in the latter. Both Gly- and Leu-NTAs did not exert any noxious effects, but they enhanced sperm mitochondrial activity in the presence and absence of oxidative stress. Moreover, NTAs (except for Leu-NTA 10 nM) tended to preserve the sperm redox balance against the injuries provoked by oxidative stress, which provide further support to the antioxidant effect of H₂S on sperm function. Both compounds also increased progressive motility over short-term incubation, which may translate into prolonged sperm survival.

CONCLUSIONS

The presence of carbonic anhydrase activity in mammalian spermatozoa makes NTAs promising molecules to investigate the role of H₂S in sperm biology. For the first time, beneficial effects of NTAs on mitochondrial activity have been found in mammalian cells in the presence and absence of oxidative stress. NTAs are interesting compounds to investigate the role of H₂S in sperm mitochondria-dependent events and to develop H₂S-related therapeutic protocols against oxidative stress in assisted reproductive technologies.

The Absolute Basophil Count

The absolute basophil count (cells/L) can be determined by manual counting of peripheral blood smears or using cell counting chambers as well as by automated hematology analyzers and fluorescence flow cytometry. Manual basophil counting of peripheral blood smears is currently regarded as the reference method, although the limitations of this method (distribution, observer, and statistical errors) are widely recognized. Automated hematology analyzers offer an advantage of larger numbers of counted cells and high throughput but are characterized by inconsistent analytical performance for basophil enumeration. Flow cytometric enumeration of circulating basophils using panels of monoclonal antibodies is being developed as novel candidate reference method for the absolute basophil count in peripheral blood. Basophil counting using fluorescence flow cytometry is characterized by high precision and statistical superiority. Emerging innovative technologies for absolute cell counts include imaging flow cytometry, mass cytometry, and on-chip blood counting, but their analytical performance for absolute basophil counts is yet to be established. Here, we describe various techniques for absolute basophil counting in peripheral blood including manual basophil counts in smears and hemocytometers and flow cytometric methodologies using double-platform, bead-based, and volumetric approaches.

Morphogo: An Automatic Bone Marrow Cell Classification System on Digital Images Analyzed by Artificial Intelligence

INTRODUCTION

The nucleated-cell differential count on the bone marrow aspirate smears is required for the clinical diagnosis of hematological malignancy. Manual bone marrow differential count is time consuming and lacks consistency. In this study, a novel artificial intelligence (AI)-based system was developed to perform cell automatic classification of bone marrow cells and determine its potential clinical applications.

MATERIALS AND METHODS

Bone marrow aspirate smears were collected from the Xinqiao Hospital of Army Medical University. First, an automated analysis system (Morphogo) scanned and generated whole digital images of bone marrow smears. Then, the nucleated marrow cells in the selected areas of the smears at a magnification of ×1,000 were analyzed by the software utilizing an AI-based platform. The cell classification results were further reviewed and confirmed independently by 2 experienced pathologists. The automatic cell classification performance of the system was evaluated using 3 categories: accuracy, sensitivity, and specificity. Correlation coefficients and linear regression equations between automatic cell classification by the AI-based system and concurrent manual differential count were calculated.

RESULTS

In 230 cases, the classification accuracy was above 85.7% for hematopoietic lineage cells. Averages of sensitivity and specificity of the system were found to be 69.4 and 97.2%, respectively. The differential cell percentage of the automated count based on 200-500 cell counts was correlated with differential cell percentage provided by the pathologists for granulocytes, erythrocytes, and lymphocytes (r ≥ 0.762, p < 0.001).

DISCUSSION/CONCLUSION

This pilot study confirmed that the Morphogo system is a reliable tool for automatic bone marrow cell differential count analysis and has potential for clinical applications. Current ongoing large-scale multicenter validation studies will provide more information to further confirm the clinical utility of the system.

Is a 500-Cell Count Necessary for Bone Marrow Differentials?: A Proposed Analytical Method for Validating a Lower Cutoff

OBJECTIVES

By convention, 500 cells are counted for bone marrow aspirate differentials. Evidence supporting such a cutoff is lacking. We hypothesized that 300-cell counts could be sufficient.

METHODS

Cell count results from 165 cases, for which values were recorded at 300 and 500 cells, were analyzed. We tested for statistical differences and changes in diagnostic classification between the two cutoffs.

RESULTS

Three hundred cell counts did not produce diagnostically different results, particularly for myeloblasts and plasma cells, where cell percentages are critical for disease classification. Method comparison analysis did not reach statistical significance for any cell type when comparing the two methods. Bias plots showed narrow, even spread about the mean bias. Contingency table analysis yielded no significant diagnostic discrepancies.

CONCLUSIONS

Performing differential counts on 300 cells would produce clinically and statistically similar results to 500 cells. Reducing the cell number counted has potential cost/labor reductions without affecting quality of care.