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Updated: Feb 6, 2026

Multiplexed Fluorescent Immunohistochemical Staining, Imaging, and Analysis in Histological Samples of Lymphoma
Published on: January 9, 2019
Quantitative chromogenic immunohistochemical image analysis in cellprofiler software
V Tollemar1, N Tudzarovski1, E Boberg2
1Division of Oral Diagnostics and Rehabilitation, Department of Dental Medicine, Karolinska Institutet, Huddinge, Sweden.
Abstract:
Visual grading of chromogenically stained immunohistochemical (IHC) samples is subjective, time consuming, and predisposed to considerable inter- and intra-observer variations. The open-source digital analysis software, CellProfiler has been extensively used for fluorescently stained cells/tissues; however, chromogenic IHC staining is routinely used in both pathological and research diagnostics. The current investigation aimed to compare CellProfiler quantitative chromogenic IHC analyses against the gold standard manual counting. Oral mucosal biopsies from patients with chronic graft-versus-host disease were stained for CD4. Digitized images were manually counted and subjected to image analysis in CellProfiler. Inter-observer and inter-platform agreements were assessed by scatterplots with linear regression and Bland-Altman plots. Validation comparisons between the manual counters demonstrated strong intra-observer concordance (r2 = 0.979), particularly when cell numbers were less than 100. Scatterplots and Bland-Altman plots demonstrated strong agreement between the manual counters and CellProfiler, with the number of positively stained cells robustly correlating (r2 = 0.938). Furthermore, CellProfiler allowed the determination of multiple variables simultaneously, such as area stained and masking to remove any nonstained tissue and white gaps, which also demonstrated reliable agreement (r2 = >0.9). CellProfiler demonstrated versatility with the ability to assess large numbers of images and allowed additional parameters to be quantified. CellProfiler allowed rapid high processing capacity of chromogenically stained chronic inflammatory tissue that was reliable, accurate, and reproducible and highlights potential applications in research diagnostics.
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