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Correspondence
Unexpected detection of various pathological features due to the careful evaluation of Cellavision (DI-60) software
  1. Marco Rosetti1,
  2. Claudia Di Carlo1,
  3. Giovanni Poletti1,
  4. Evita Massari1,
  5. Marta Monti1,
  6. Giuseppe Romano2,
  7. Virginia Libri1,
  8. Melania Olivieri1,
  9. Valentina Polli1,
  10. Luca Baldrati1,
  11. Stefania Valenti1,
  12. Tommaso Fasano1
  1. 1 Clinical Pathology Unit, AUSL della Romagna, Pievesestina-Cesena, Italy
  2. 2 Emergency Department, AUSL della Romagna, Cesena, Italy
  1. Correspondence to Dr Marco Rosetti, Clinical Pathology Unit, AUSL della Romagna, Pievesestina, 47522, Italy; marco.rosetti{at}auslromagna.it

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The evaluation of the full blood count and blood smears certainly represents one of the main activities performed by a clinical pathology laboratory. Major manufacturers of haematology analysers are investing in the digitalisation of blood smears and in software capable of autonomously classifying morphological alterations.1 2 Haematological digital morphological technology has only been recently introduced, the first installations were implemented no more than 20 years ago,3 and, therefore, the analysis of its advantages and disadvantages is constantly evolving.2 4–6 The diffusion of its use in an increased number of laboratories highlights new perspectives. The Clinical Pathology Unit of the Romagna Health Service (Italy) is organised in a network of eight laboratories (one hub and seven spokes), each of them equipped with a digital morphological analyser (DI-60 Sysmex, Kobe, Japan) employing CellaVision software (CellaVision AB, Lund, Sweden), which allows remote blood smear assessment.7 The DI-60/Cellavision was set to the automatic preclassification mode in order to acquire 200 white blood cells, to classify them into 14 subtypes of ‘leucocytes’ (unidentified cell, neutrophil, lymphocyte, monocyte, eosinophil, basophil, promyelocyte, myelocyte, metamyelocyte, promonocyte, prolymphocyte, blast, plasma cell, hairy cell), and 5 subtypes of ‘non-leucocytes’ (erythroblast, …

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Footnotes

  • Handling editor Runjan Chetty.

  • Contributors MR designed the study, analysed the data, drafted the paper. CDC analysed some digital patients’ data, drafted the paper. GP designed the study, analysed patients’ the data, drafted the paper. EM analysed some digital patients’ data, drafted the paper. MM analysed the data, drafted the paper. GR analysed patients’ the data. VL, MO, VP and LB analysed some digital patients’ data. SV drafted the paper. TF drafted the paper and revise it, approved the submitted version of the paper.

  • 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; internally peer reviewed.