3D image analysis reveals differences of CD30 positive cells and network formation in reactive and malignant human

Julia Liebers1, Patrick Wurzel2, Kerstin Bianca Reisinger1

  • 1Reference and Consultant Center of Lymph Node and Lymphoma Pathology at Dr. Senckenberg Institute for Pathology, Frankfurt/Main, Hessen, Germany.

Plos One
|October 25, 2019
PubMed

Insights

Three-dimensional imaging reveals distinct characteristics of CD30+ cells in classical Hodgkin lymphoma (cHL) compared to reactive cells. This advanced technique offers new diagnostic insights into cell volume, shape, and network formation in cHL.

Area of Science:

  • Pathology
  • Immunohistochemistry
  • 3D Imaging

Background:

  • Histological sections are the gold standard in diagnostic pathology.
  • Key diagnostic criteria include nuclear morphology, chromatin, nucleus-cytoplasm ratio, and protein expression.
  • CD30 is an important marker in lymphoid tissues.

Purpose of the Study:

  • To evaluate the benefits and drawbacks of 3D imaging for CD30+ cells in classical Hodgkin Lymphoma (cHL).
  • To compare 3D characteristics of CD30+ cells in cHL with CD30+ cells in reactive lymphoid tissues.

Main Methods:

  • Immunofluorescence confocal microscopy and computer-based analysis were employed.
  • CD30+ neoplastic cells in Nodular Sclerosis cHL (NScCHL) and Mixed Cellularity cHL (MCcHL) were compared.
  • CD30+ reactive cells in Adenoids (AD) and Lymphadenitis (LAD) served as controls.

Main Results:

  • 3D imaging enabled calculation of CD30+ cell volume percentages.
  • CD30+ cell volume was significantly higher in cHL (up to 8% in NScHL) compared to reactive tissues (1.5-2%).
  • CD30+ tumor cells (HRS-cells) in cHL exhibited larger volumes, more protrusions, and formed distinct large cell networks, particularly in NScHL.

Conclusions:

  • 3D laser scanning provides visualization of complete cells, their interactions, and spatial distribution, surpassing 2D histology.
  • The ability to differentiate cells by volume, surface, shape, and cluster formation offers novel diagnostic and biological insights.
  • 3D imaging provides increased data for bioinformatical analysis, enhancing pathological diagnostics.
Abstract

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