Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Classification of Leukocytes01:30

Classification of Leukocytes

Leukocytes are classified into two groups based on the presence or absence of cytoplasmic granules. Granular leukocytes, which contain granules, belong to the myeloid lineage and are divided into three subtypes: neutrophils, eosinophils, and basophils. These cells are roughly spherical and characterized by the granules in their cytoplasm.
Neutrophils are the most abundant type of granular leukocytes, comprising 50-70% of all leukocytes. They feature small, evenly distributed granules and a...
Classification of Epithelial Tissues: Overview01:22

Classification of Epithelial Tissues: Overview

Epithelial tissues are classified according to the shape of the cells and the number of cell layers formed. Cell shapes can be squamous (flattened and thin), cuboidal (square-like, as wide as it is tall), or columnar (rectangular, taller than it is wide). Additionally, the nucleus shape helps identify the type of epithelial cells. Squamous cells have flattened disc-shaped nuclei, cuboidal cells have spherical nuclei, and columnar cells have elongated nuclei.
Based on the number of cell layers,...
Lymphoid Cells and Tissues01:18

Lymphoid Cells and Tissues

Lymphoid cells and tissues are integral to the immune system, which is crucial in maintaining our body's defense against harmful pathogens. They form the building blocks of lymphoid organs, which include the spleen, thymus, and lymph nodes.
Lymphoid cells consist of various types of immune system cells. These include B and T lymphocytes, which are responsible for producing antibodies and killing infected cells, respectively. Dendritic cells act as messengers between the innate and adaptive...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Splenic silicosis, a rare extrapulmonary manifestation of occupational silica exposure: A case report.

Multidisciplinary respiratory medicine·2026
Same author

Diagnostic Utility of PRAME Immunohistochemistry for Distinguishing Acral Melanoma From Acral Melanocytic Nevi.

Journal of cutaneous pathology·2026
Same author

Lymphomatoid papulosis type D with γδ phenotype evolving from pityriasis lichenoides in a pediatric patient.

JAAD case reports·2026
Same author

A case report of cutaneous <i>Brugia</i> <i>pahangi</i> infection presenting with recurrent lymphangitis and a subcutaneous nodule.

JAAD case reports·2026
Same author

A rare and complex case report of superimposed clostridial spondylodiscitis and epidural abscess associated with spinal lymphoma of the thoracic spine.

BMC infectious diseases·2026
Same author

Genomic profiling and therapeutic targets of Thai melanoma revealed by next-generation sequencing.

Scientific reports·2026

Related Experiment Video

Updated: Jul 13, 2026

Multiplexed Fluorescent Immunohistochemical Staining, Imaging, and Analysis in Histological Samples of Lymphoma
07:52

Multiplexed Fluorescent Immunohistochemical Staining, Imaging, and Analysis in Histological Samples of Lymphoma

Published on: January 9, 2019

Pitfalls in classifying lymphomas.

Tawatchai Pongpruttipan1, Panitta Sitthinamsuwan, Pimpattana Rungkaew

  • 1Department of Pathology, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok 10700, Thailand. watpptp@yahoo.com

Journal of the Medical Association of Thailand = Chotmaihet Thangphaet
|July 13, 2007
PubMed
Summary

Lymphoma classification pitfalls are common, especially for MALT lymphoma and Hodgkin lymphoma subtypes. Hematopathology expertise significantly reduces misdiagnosis rates for most lymphoma types.

More Related Videos

Label-Free Identification of Lymphocyte Subtypes Using Three-Dimensional Quantitative Phase Imaging and Machine Learning
08:58

Label-Free Identification of Lymphocyte Subtypes Using Three-Dimensional Quantitative Phase Imaging and Machine Learning

Published on: November 19, 2018

From a 2DE-Gel Spot to Protein Function: Lesson Learned From HS1 in Chronic Lymphocytic Leukemia
10:18

From a 2DE-Gel Spot to Protein Function: Lesson Learned From HS1 in Chronic Lymphocytic Leukemia

Published on: October 19, 2014

Related Experiment Videos

Last Updated: Jul 13, 2026

Multiplexed Fluorescent Immunohistochemical Staining, Imaging, and Analysis in Histological Samples of Lymphoma
07:52

Multiplexed Fluorescent Immunohistochemical Staining, Imaging, and Analysis in Histological Samples of Lymphoma

Published on: January 9, 2019

Label-Free Identification of Lymphocyte Subtypes Using Three-Dimensional Quantitative Phase Imaging and Machine Learning
08:58

Label-Free Identification of Lymphocyte Subtypes Using Three-Dimensional Quantitative Phase Imaging and Machine Learning

Published on: November 19, 2018

From a 2DE-Gel Spot to Protein Function: Lesson Learned From HS1 in Chronic Lymphocytic Leukemia
10:18

From a 2DE-Gel Spot to Protein Function: Lesson Learned From HS1 in Chronic Lymphocytic Leukemia

Published on: October 19, 2014

Area of Science:

  • Hematopathology
  • Oncology
  • Diagnostic Pathology

Background:

  • The World Health Organization (WHO) classification (2001) for lymphomas necessitates comprehensive data, yet misdiagnosis remains a challenge in resource-limited settings.
  • Limited antibody panels for immunophenotyping can contribute to diagnostic errors in lymphoma classification.

Purpose of the Study:

  • To identify and analyze diagnostic pitfalls in lymphoma classification among hematopathologists, general pathologists, and pathology residents.
  • To evaluate the impact of limited resources on lymphoma diagnostic accuracy.

Main Methods:

  • A retrospective review of 104 newly diagnosed lymphoma cases from Siriraj Hospital (July 2002-June 2003).
  • Two rounds of individually blinded review by a hematopathologist, two general pathologists, and three pathology residents.
  • Consensus-based final diagnoses were established, and pitfalls were quantified by frequency of misdiagnosis.

Main Results:

  • Diffuse large B-cell lymphoma (DLBCL) and subcutaneous panniculitis-like T-cell lymphoma (SPTCL) showed low diagnostic pitfalls (8%).
  • Significant pitfalls were observed in MALT lymphoma (60%), mixed cellularity Hodgkin lymphoma (50%), and Burkitt lymphoma (33%).
  • Hematopathologists demonstrated lower pitfalls, particularly in uncommon lymphoma types, compared to non-hematopathologists.

Conclusions:

  • Diagnostic pitfalls in lymphoma classification are frequent and pose a clinical challenge.
  • Specialized interest and expertise in hematopathology are crucial for reducing misdiagnosis in lymphomas, excluding DLBCL.