Plasma cell quantification in bone marrow by computer-assisted image analysis.
Minor and major criteria for the diagnosis of multiple meloma according to the definition of the WHO classification include different categories of the bone marrow plasma cell count: a shift from the 10-30% group to the > 30% group equals a shift from a minor to a major criterium, while the < 10% group does not contribute to the diagnosis. Plasma cell fraction in the bone marrow is therefore critical for the classification and optimal clinical management of patients with plasma cell dyscrasias. The aim of this study was (i) to establish a digital image analysis system able to quantify bone marrow plasma cells and (ii) to evaluate two quantification techniques in bone marrow trephines i.e. computer-assisted digital image analysis and conventional light-microscopic evaluation. The results were compared regarding inter-observer variation of the obtained results.



Eighty-seven patients, 28 with multiple myeloma, 29 with monoclonal gammopathy of undetermined significance, and 30 with reactive plasmocytosis were included in the study. Plasma cells in H&E- and CD138-stained slides were quantified by two investigators using light-microscopic estimation and computer-assisted digital analysis. The sets of results were correlated with rank correlation coefficients. Patients were categorized according to WHO criteria addressing the plasma cell content of the bone marrow (group 1: 0-10%, group 2: 11-30%, group 3: > 30%), and the results compared by kappa statistics.



The degree of agreement in CD138-stained slides was higher for results obtained using the computer-assisted image analysis system compared to light microscopic evaluation (corr.coeff. = 0.782), as was seen in the intra- (corr.coeff. = 0.960) and inter-individual results correlations (corr.coeff. = 0.899). Inter-observer agreement for categorized results (SM/PW: kappa 0.833) was in a high range.



Computer-assisted image analysis demonstrated a higher reproducibility of bone marrow plasma cell quantification. This might be of critical importance for diagnosis, clinical management and prognostics when plasma cell numbers are low, which makes exact quantifications difficult.
Went
P
P
Institute for Pathology, University of Basel, University Hospital, Schönbeinstrasse 40, 4031 Basel, Switzerland. pwent@uhbs.ch
Mayer
S
S
Oberholzer
M
M
Dirnhofer
S
S
D000465:Algorithms; D001706:Biopsy; D001854:Bone Marrow Cells / Q000166:cytology* / Q000378:metabolism; D003201:Computers; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D007150:Immunohistochemistry; D008562:Membrane Glycoproteins / Q000096:biosynthesis; D009101:Multiple Myeloma / Q000473:pathology; D015588:Observer Variation; D010265:Paraproteinemias / Q000473:pathology; D010950:Plasma Cells / Q000166:cytology*; D011509:Proteoglycans / Q000096:biosynthesis; D012189:Retrospective Studies; D053668:Syndecan-1; D053667:Syndecans
D008562:Membrane Glycoproteins; D011509:Proteoglycans; C508241:SDC1 protein, human; D053668:Syndecan-1; D053667:Syndecans