Evaluation of Efficacy of White Blood Cell Identification in Peripheral Blood by Automated Scanning of Stained Blood Smear Images with Variable Magnification

Sosnin, D. Yu.; Onyanova, L. S.; Kubarev, O. G.; Kozonogova, Elena

doi:10.1007/s10527-018-9776-1

Cited by 3 publications

(2 citation statements)

References 8 publications

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“…Additionally, our results showed good agreement between the percentages of normal WBC in pre‐ and post‐classification, quantified by high values of correlation and concordance (between 0.91 and 1). These results are comparable to those obtained with other digital cell morphology analysers as reported by several studies 10,23–26 …”

Section: Discussionsupporting

confidence: 91%

“…These results are comparable to those obtained with other digital cell morphology analysers as reported by several studies. 10,[23][24][25][26] A second aspect to discuss is the MC-80 performance for the DLC obtained on abnormal samples. Abnormal cells are difficult to identify, especially blast cells and ALC, as reported in some external quality control surveys.…”

Section: Discussionmentioning

confidence: 99%

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

Merino,

Laguna,

Rodríguez‐García

et al. 2023

Int J Lab Hematology

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IntroductionMindray 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.MethodsA 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.ResultsThe 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.ConclusionWe found that the MC‐80 shows high performance for WBC differentials for both normal samples and patients with haematological diseases.

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Section: Discussionsupporting

confidence: 91%

Section: Discussionmentioning

confidence: 99%

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

Merino,

Laguna,

Rodríguez‐García

et al. 2023

Int J Lab Hematology

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RETRACTED ARTICLE: Interpolative Leishman-Stained transformation invariant deep pattern classification for white blood cells

Karthikeyan

Venkatesan

2020

Soft Comput

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Morphology of Neutrophil Granulocytes in Norm and Pathology

Sosnin,

Bazarnyi

2023

Laboratornaya I Klinicheskaya Meditsina. Farmatsiya

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A literature review describing the morphological features of normal neutrophils and their changes in various diseases is presented. Parameters of neutrophil granulocyte nuclei are described, changes in nuclei are characterized in congenital and acquired pathology. The characteristics of the cytoplasm of normal neutrophils and its changes in pathological conditions are also given. Various types of cytoplasmic inclusions present in normal cells and formed in both hereditary and acquired diseases are described in detail. The problems of clinical and diagnostic significance of changes in the morphology of neutrophils are discussed.

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Evaluation of Efficacy of White Blood Cell Identification in Peripheral Blood by Automated Scanning of Stained Blood Smear Images with Variable Magnification

Cited by 3 publications

References 8 publications

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

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

RETRACTED ARTICLE: Interpolative Leishman-Stained transformation invariant deep pattern classification for white blood cells

Morphology of Neutrophil Granulocytes in Norm and Pathology

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