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Updated: Jun 25, 2025
Multiplexed Fluorescent Immunohistochemical Staining, Imaging, and Analysis in Histological Samples of Lymphoma
Published on: January 9, 2019
Morphology and multiparameter flow cytometry combined for integrated lymphoma diagnosis on small volume samples:
Mats Ehinger1,2, Marie C Béné3
1Division of Pathology, Department of Clinical Sciences Lund, Lund University, Lund, Sweden. mats.ehinger@med.lu.se.
Insights
Accurate lymphoma diagnosis is achievable with small tissue samples like needle biopsies. Integrating morphology, immunohistochemistry, and flow cytometry, along with AI, enhances diagnostic capabilities for challenging cases.
Area of Science:
- Hematopathology
- Oncology
- Diagnostic Pathology
Background:
- Lymphoma diagnosis traditionally relies on surgical biopsies.
- Minimally invasive techniques yield smaller samples, posing diagnostic challenges.
- Current trends favor less invasive procedures, necessitating adapted diagnostic strategies.
Purpose of the Study:
- To review the diagnostic possibilities and limitations of small volume lymphoma specimens.
- To discuss the roles of histology, cytology, and flow cytometry in diagnosing lymphoma from limited material.
- To highlight the benefits of an integrated diagnostic approach and future directions, including AI.
Main Methods:
- Review of current literature on lymphoma diagnosis using small biopsy samples.
- Discussion of morphological, immunohistochemical, and multiparameter flow cytometry techniques.
- Analysis of diagnostic approaches for core needle biopsies and fine needle aspirations.
Main Results:
- Accurate lymphoma diagnosis is often feasible with small volume material.
- An integrated approach combining histology, cytology, and flow cytometry is crucial.
- Handling and analysis of small specimens require specialized techniques.
Conclusions:
- Despite challenges, small volume biopsies can yield accurate lymphoma diagnoses.
- An integrated diagnostic strategy is essential for optimal patient care.
- Emerging technologies like artificial intelligence show promise for future lymphoma diagnostics.
Abstract:
The diagnosis of lymphoma relies mainly on clinical examination and laboratory explorations. Among the latter, morphological and immunohistochemical analysis of a tissue biopsy are the cornerstones for proper identification and classification of the disease. In lymphoma with blood and/or bone marrow involvement, multiparameter flow cytometry is useful. This technique can also be applied to fresh cells released from a biopsy sample. For full comprehension of lymphomas, surgical biopsies are best and indeed recommended by the hematopathological community. Currently, however, there is a global trend towards less invasive procedures, resulting in smaller samples such as core needle biopsies or fine needle aspirations which can make the diagnosis quite challenging. In this review, the possibilities and limitations to make an accurate lymphoma diagnosis on such small volume material are presented. After recalling the major steps of lymphoma diagnosis, the respective value of histology, cytology, and flow cytometry is discussed, including handling of small specimens. The benefits of an integrated approach are then evoked, followed by discussion about which attitude to adopt in different contexts. Perhaps contrary to the prevailing view among many pathologists, a full diagnosis on small volume material, combined with relevant ancillary techniques, is often possible and indeed supported by recent literature. A glimpse at future evolutions, notably the merit of artificial intelligence tools, is finally provided. All in all, this document aims at providing pathologists with an overview of diagnostic possibilities in lymphoma patients when confronted with small volume material such as core needle biopsies or fine needle aspirations.
