Design and clinical results of Hematrak: an automated differential counter

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.

A Novel Automated Slide-Based Technology for Visualization, Counting, and Characterization of the Formed Elements of Blood: A Proof of Concept Study

Context.—

A novel automated slide-based approach to the complete blood count and white blood cell differential count is introduced.

Objective.—

To present proof of concept for an image-based approach to complete blood count, based on a new slide preparation technique. A preliminary data comparison with the current flow-based technology is shown.

Design.—

A prototype instrument uses a proprietary method and technology to deposit a precise volume of undiluted peripheral whole blood in a monolayer onto a glass microscope slide so that every cell can be distinguished, counted, and imaged. The slide is stained, and then multispectral image analysis is used to measure the complete blood count parameters. Images from a 600-cell white blood cell differential count, as well as 5000 red blood cells and a variable number of platelets, that are present in 600 high-power fields are made available for a technologist to view on a computer screen. An initial comparison of the basic complete blood count parameters was performed, comparing 1857 specimens on both the new instrument and a flow-based hematology analyzer.

Results.—

Excellent correlations were obtained between the prototype instrument and a flow-based system. The primary parameters of white blood cell, red blood cell, and platelet counts resulted in correlation coefficients (r) of 0.99, 0.99, and 0.98, respectively. Other indices included hemoglobin (r = 0.99), hematocrit (r = 0.99), mean cellular volume (r = 0.90), mean corpuscular hemoglobin (r = 0.97), and mean platelet volume (r = 0.87). For the automated white blood cell differential counts, r values were calculated for neutrophils (r = 0.98), lymphocytes (r = 0.97), monocytes (r = 0.76), eosinophils (r = 0.96), and basophils (r = 0.63).

Conclusions.—

Quantitative results for components of the complete blood count and automated white blood cell differential count can be developed by image analysis of a monolayer preparation of a known volume of peripheral blood.

Segmentation of complex cell clusters in microscopic images: Application to bone marrow samples

BACKGROUND

Morphologic examination of bone marrow and peripheral blood samples continues to be the cornerstone in diagnostic hematology. In recent years, interest in automatic leukocyte classification using image analysis has increased rapidly. Such systems collect a series of images in which each cell must be segmented accurately to be classified correctly. Although segmentation algorithms have been developed for sparse cells in peripheral blood, the problem of segmenting the complex cell clusters characterizing bone marrow images is harder and has not been addressed previously.

METHODS

We present a novel algorithm for segmenting clusters of any number of densely packed cells. The algorithm first oversegments the image into cell subparts. These parts are then assembled into complete cells by solving a combinatorial optimization problem in an efficient way.

RESULTS

Our experimental results show that the algorithm succeeds in correctly segmenting densely clustered leukocytes in bone marrow images.

CONCLUSIONS

The presented algorithm enables image analysis-based analysis of bone marrow samples for the first time and may also be adopted for other digital cytometric applications where separation of complex cell clusters is required.

Adaptation of the May-Grünwald-Giemsa staining method for automated differential counting of blood leukocytes by a Hematrak analyzer

The selection of exact pH (6.85/6.90) concentrations of the stains and staining times made it possible to use the May-Grünwald-Giemsa (MGG) staining method for smears studied with a Hematrak model 240 automated differential leucocyte counter. The differences between the smears stained by the method of Wright according to the recommendations of the manufacturer and the present MGG-modification resulted in non-significant differences in the recognition of various types of leucocytes. The differences between the manual method and those obtained by Hematrak for the MGG-stained samples with normal total leucocyte counts were nonsignificant with all types of leucocytes except basophils, which were underestimated by the instrument. The present staining procedure was adequate in studying of neutrophilias. When samples with lymphocytosis or with immature cells were examined, too few lymphocytes and immature cells and too many monocytes were obtained by the instrument, as compared to the manual method.

Differentiation of granulocytes in Pappenheim stained blood cell smears using standardized cytophotometric analysis

The well-known problems of the low reproducibility of peripheral blood smear analysis have for some time stimulated endeavours to automate blood cell classification. In the cytophotometric standardized color measurement and analysis, the computed color characteristics for the first time refer to an internationally accepted color system, allowing not only an international comparison of the computer color measurements but an unproblematic mutual interchange of color information between man and machine based on both the human visual color impressions and the conventional morphological color attributes of the white blood cells. The discriminatory power of the method is demonstrated by differentiating the cytoplasm granulations in basophil, eosinophil and neutrophil granulocytes.