Related Experiment Video
Updated: Aug 7, 2026
Automated Quantification of Hematopoietic Cell – Stromal Cell Interactions in Histological Images of Undecalcified Bone
Published on: April 8, 2015
Plasma cell quantification in bone marrow by computer-assisted image analysis
P Went1, S Mayer, M Oberholzer
1Institute for Pathology, University of Basel, University Hospital, Schönbeinstrasse 40, 4031 Basel, Switzerland. pwent@uhbs.ch
Background:
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.
Material And Methods:
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.
Results:
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.
Conclusions:
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.
Insights
Computer-assisted image analysis offers more reproducible bone marrow plasma cell quantification than traditional methods. This improved accuracy is crucial for diagnosing and managing plasma cell disorders, especially when cell counts are low.
Area of Science:
- Hematology
- Medical Diagnostics
- Computational Pathology
Background:
- Accurate bone marrow plasma cell quantification is critical for diagnosing plasma cell dyscrasias per WHO classification.
- Plasma cell counts in bone marrow trephines influence diagnostic criteria and patient management.
- Existing methods for plasma cell quantification have limitations in reproducibility.
Purpose of the Study:
- To develop and validate a digital image analysis system for quantifying bone marrow plasma cells.
- To compare the accuracy and reproducibility of computer-assisted analysis versus conventional light microscopy.
- To assess inter-observer variation in plasma cell quantification techniques.
Main Methods:
- Eighty-seven patients with multiple myeloma, monoclonal gammopathy of undetermined significance, and reactive plasmocytosis were included.
- Plasma cells were quantified in H&E- and CD138-stained bone marrow trephines using light microscopy and digital image analysis.
- Results were correlated using rank correlation coefficients and compared using kappa statistics for WHO categorization.
Main Results:
- Computer-assisted digital image analysis showed higher agreement for CD138-stained slides (corr.coeff. = 0.782) compared to light microscopy.
- Excellent intra- (corr.coeff. = 0.960) and inter-individual (corr.coeff. = 0.899) correlations were observed with the digital analysis system.
- High inter-observer agreement (kappa 0.833) was achieved for categorized results.
Conclusions:
- Computer-assisted image analysis provides superior reproducibility for bone marrow plasma cell quantification.
- This enhanced reproducibility is vital for accurate diagnosis, clinical management, and prognostics, particularly in cases with low plasma cell numbers.
- Digital image analysis holds significant potential for improving the precision of plasma cell quantification in hematological diagnostics.
