Article Text
Abstract
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.
- automation
- cell count
- haematology
- morphological and microscopic findings
Data availability statement
All data relevant to the study are included in the article.
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Data availability statement
All data relevant to the study are included in the article.
Footnotes
Handling editor Mary Frances McMullin.
Contributors All authors confirmed that they have contributed to the intellectual content of this paper and have met the following three requirements: (1) significant contributions to the conception and design, acquisition of data or analysis and interpretation of data; (2) drafting or revising the article for intellectual content and (3) final approval of the published article.
Funding The authors have not declared a specific grant for this research from any funding agency in the public, commercial or not-for-profit sectors.
Competing interests None declared.
Provenance and peer review Not commissioned; externally peer reviewed.