Validation of a QuPath-Based Artificial Intelligence Workflow for Plasma Cell Quantification on CD138
Mohammed N Meera1, Ankur Ahuja1, Venkatesan Somasundaram1
1Department of Pathology, Armed Forces Medical College, Pune, India.
Introduction:
Plasma cell percentage on CD138 immunohistochemistry of bone marrow trephine biopsies is fundamental to the diagnosis and risk stratification of plasma cell neoplasms, yet manual visual estimation is subject to inter-observer variability. We report a single-center pilot validation of an AI-assisted whole-section workflow using the open-source platform QuPath v0.6 against conventional manual methods in an Indian tertiary hematopathology setting.
Methods:
Fifty consecutive CD138-immunostained trephine biopsies were independently assessed by (A) overview estimation by three hematopathologists, (B) digital whole-section analysis with QuPath v0.6 on whole-slide images acquired with the OptraScan OS-Ultra scanner, and (C) systematic cell-by-cell manual count by the principal investigator (reference standard). Concordance was assessed by Spearman ρ, intraclass correlation coefficient (ICC), Lin's concordance correlation coefficient (CCC), Bland-Altman analysis, Passing-Bablok regression, and weighted Cohen's κ. Diagnostic performance of Method B was evaluated at the International Myeloma Working Group (IMWG) thresholds of 10%, 30%, and 60%.
Results:
Method B versus Method C showed ICC = 0.995 (95% CI, 0.97-1.00), Lin's ρc = 0.995, Spearman ρ = 0.989, Bland-Altman bias +2.4 percentage points (95% limits of agreement -3.0 to +7.8). Passing-Bablok regression gave slope 1.025 (95% CI, 1.00-1.06) and intercept +1.54, indicating absence of proportional bias. Diagnostic performance at IMWG thresholds was excellent (area under the curve (AUC) 0.995-1.000; sensitivity 100% at every threshold). Weighted Cohen's κ for three-grade burden classification was 0.91 with no extreme misclassifications.
Conclusion:
AI-assisted QuPath-based whole-section plasma cell quantification using CD138 immunohistochemistry achieves excellent concordance with manual reference counting and strong diagnostic performance across all clinically decisive IMWG thresholds.
