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Updated: May 2, 2026
Multiplexed Fluorescent Immunohistochemical Staining, Imaging, and Analysis in Histological Samples of Lymphoma
Published on: January 9, 2019
"High Content Imaging for the Morphometric Diagnosis and Immunophenotypic Prognosis of Canine Lymphomas"
Stratos Papakonstantinou1, Peter James O'Brien
1Veterinary Pathobiology Section, School of Veterinary Medicine, University College Dublin, Ireland.
Insights
High Content Imaging (HCI) offers a novel, semi-automated method for diagnosing canine lymphoma by analyzing lymphocyte morphology. This technology also determines prognostic immunophenotype, improving diagnostic accuracy for veterinary professionals.
Area of Science:
- Veterinary diagnostics
- Biomedical imaging
- Cell biology
Background:
- Canine lymphoma diagnosis is typically manual and qualitative, relying on lymphocyte size.
- Immunophenotype is crucial for prognosis but requires dual-antibody labeling.
- High Content Imaging (HCI) is an advanced microscopy technique for quantitative analysis.
Purpose of the Study:
- To evaluate HCI's capability in semi-automating quantitative diagnosis of canine lymphoma.
- To determine if HCI can simultaneously assess prognostic immunophenotype.
- To identify novel morphometric parameters for lymphoma diagnosis.
Main Methods:
- Lymphocytes from healthy and lymphoma-affected dogs were analyzed using HCI.
- Cells were stained with antibodies for T and B cell identification (CD3, CD21) and Hoechst-33342.
- Morphological parameters including cell area, nuclear area, and roundness were quantified.
Main Results:
- HCI successfully discriminated between benign and malignant lymphocytes.
- Significant differences in cell area, nuclear displacement, and roundness were observed between groups.
- HCI provided simultaneous immunophenotypic information for prognosis.
Conclusions:
- HCI offers a novel, semi-automated approach for diagnosing canine lymphoma.
- Identified morphometric parameters provide effective diagnostic and prognostic capabilities.
- This technology has the potential to enhance veterinary diagnostic accuracy.
Abstract:
Background: The common, symptomatic form of canine lymphoma (multicentric, medium-to-large cell, advanced) is consistently diagnosed manually and qualitatively by veterinary cytologists based on increased lymphocyte size. The most effective prognostic feature is immunophenotype based on dual-antibody labeling for T versus B cells. High Content Imaging (HCI) is a novel, semi-automated, fluorescence microscopy and image-analysis technology used in research and predictive toxicology. Objective: We tested the hypothesis that HCI could semi-automatise the quantitative diagnosis of canine lymphoma and simultaneously determine immunophenotypic prognosis. Methods: Lymphocytes were obtained from lymph nodes of 6 lymphoma-free and 5 lymphomatous dogs, stained with antibodies against CD21 and CD3 (B- vs. T- cells), Hoechst-33342 and seeded into 96-well plates. Morphological parameters were examined: a) cell area, b) nuclear area, c) nuclear displacement, d) cytoplasmic area, e) nucleus to cell area ratio (N/Cell), f) nucleus to cytoplasm ratio (N/Cyt), g) cell roundness. Results: HCI unequivocally discriminated malignant from benign lymphocytes, and provided immunophenotype. Cell and cytoplasmic area, nuclear displacement and roundness showed biggest differences without value overlap between groups. Mean/ median/SD for control versus lymphoma samples were: a) cell area (µm2 ): 55.5/53.6/7.5 versus 80.3/75.5/8.7, b) nuclear area (µm2 ): 33.4/34.8/3.5 versus 40.2/38.5/5, c) cytoplasm area (µm2 ): 22.1/216.2 versus 40/38.4/4.9, d) N/Cell: 0.62/0.62/0.06 versus 0.52/0.52/0.03, e) nuclear displacement (arbitrary units): 0.139/0.149/0.055 versus 0.33/0.30//0.056, f) N/Cyt: 1.84/1.76/0.44 versus 1.19/1.24/0.17, g) roundness index: 1.22/1.21/0.03 versus 1.42/ 1.42/0.11 (p<0.05). Conclusion: HCI identified several, novel, morphometric parameters that effectively diagnose the common, symptomatic form of canine lymphoma, and also simultaneously determine prognostic immunophenotype. © 2014 Clinical Cytometry Society.
