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Related Concept Videos

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,...
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Simple epithelium consists of a single layer of cells that lines body cavities and blood vessels. The shape of the cells in the epithelium reflects the function of the tissue. Cells in simple squamous epithelium appear as thin scales with flat, elliptical nuclei that mirror the form of the cell.
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Classification of Epithelial Tissues: Stratified Epithelium01:29

Classification of Epithelial Tissues: Stratified Epithelium

Stratified epithelium consists of several stacked layers of cells. They provide the durability to withstand constant physical and chemical attacks. Stratified epithelium is named after the shape of the most apical layer of cells. Stratified squamous epithelium is the most common type found in the human body. In this tissue, the apical cells are squamous, whereas the basal layer contains either columnar or cuboidal cells. The basal cells divide to form new daughter cells, which gradually become...
Classification of Leukocytes01:30

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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...

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NBI Classification Optimization With Morphological Characteristics in Vocal Fold Leukoplakia.

Yi Fang1,2, Changjiang Li1,2, Min Chen1,2

  • 1ENT Institute and Department of Otorhinolaryngology, Eye & ENT Hospital, Fudan University, Shanghai, China.

Ear, Nose, & Throat Journal
|August 31, 2024
PubMed
Summary
This summary is machine-generated.

Predicting vocal fold leukoplakia (VFL) pathology is challenging. Irregular or rough VFL texture, identified via narrow-band imaging (NBI), significantly predicts high-risk lesions, aiding in early diagnosis.

Keywords:
NBIclassificationmorphologypathologyvocal fold leukoplakia

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Area of Science:

  • Otolaryngology
  • Pathology
  • Medical Imaging

Background:

  • Vocal fold leukoplakia (VFL) presents diagnostic challenges.
  • Accurate pathological prediction is crucial for effective treatment of VFL.
  • Narrow-band imaging (NBI) offers enhanced visualization of laryngeal lesions.

Purpose of the Study:

  • To evaluate the role of NBI classification (Type II) and morphological features in predicting VFL pathology.
  • To correlate laryngoscopic findings with histopathological outcomes.
  • To improve the diagnostic accuracy for high-risk VFL.

Main Methods:

  • Retrospective analysis of 59 VFL patients with NBI Type II classification.
  • Histopathological classification based on 2005 WHO Blue Book criteria (low-risk: non-, mild, moderate dysplasia; high-risk: severe dysplasia).
  • Morphological assessment using laryngoscopic scoring for texture, size, and lesion thickness.

Main Results:

  • Pathologies included non-dysplasia, mild, moderate, severe dysplasia, and carcinoma.
  • Rough VFL texture was significantly associated with high-risk pathologies (severe dysplasia and carcinoma).
  • Irregular texture, large size, and thick lesions were identified as predictors of high-risk VFL.

Conclusions:

  • Pathological prediction of VFL Type II using NBI alone is difficult.
  • Morphological characteristics, particularly irregular/rough texture, are valuable predictors of high-risk VFL.
  • Integrating morphological assessment with NBI can enhance pathological prediction for VFL.