IngentaConnect Differential counting of blood leukocytes using automated microsc...

Authors: Swolin B.¹; Simonsson P.²; Backman S.³; Löfqvist I.²; Bredin I.¹; Johnsson M.³

Source: Clinical & Laboratory Haematology, Volume 25, Number 3, June 2003 , pp. 139-147(9)

Abstract:

Summary

The morphological appearance of blood cells has an established association to clinical conditions. A novel system, DiffMaster^TM Octavia for differential counting of blood leukocytes, has been evaluated. The system consisted of a microscope, 3-chip color charge coupled device (CCD) camera, automated motorized stage holder, electronic hardware for motor and light control and software for automatic cell location and image processing for preclassification of blood cells using artificial neural networks. The DiffMaster test method, was evaluated on 322 routine blood samples (400 cells per sample) using manual microscopy as reference method. The results showed a correlation of determination (r²) of 0.8–0.98 for the normal cell classes and blast cells. The DiffMaster correctly preclassified 89% of all leukocytes with a good reproducibility. After verification of the cell classes, the agreement between the test and reference method was 91% whether the sample was abnormal or normal. The clinical sensitivity was 98% and specificity 82%. The sensitivity to identify blast cells was slightly higher with the DiffMaster than manual microscopy. Similar levels of short-term imprecision for the two methods were found for all cell classes. In conclusion this study shows that the DiffMaster can provide a decision support system which, together with a qualified morphologist, can generate leukocyte differential count reports of high quality.

Keywords: Artificial neural networks; automation; image analysis; leukocyte differential; microscopy

Document Type: Research article

DOI: 10.1046/j.1365-2257.2003.00516.x

Affiliations: 1: Department of Clinical Chemistry and Transfusion Medicine, Sahlgrenska University hospital, Göteborg University, Sweden 2: Department of Clinical Chemistry, Malmö University hospital, Lund University, Sweden 3: Cella Vision AB, Ideon Research Park, Lund, Sweden

The full text article is available for purchase

$54.87 plus tax

Differential counting of blood leukocytes using automated microscopy and a decision support system based on artificial neural networks – evaluation of DiffMasterTM Octavia

Differential counting of blood leukocytes using automated microscopy and a decision support system based on artificial neural networks – evaluation of DiffMaster^TM Octavia