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A method for quantifying limbal stem cell niches using OCT imaging.

Michel Haagdorens1,2, Joséphine Behaegel1,3, Jos Rozema1,2

  • 1Faculty of Medicine and Health Sciences, Department of Ophthalmology, Visual Optics and Visual Rehabilitation, Antwerp University, Antwerp, Wilrijk, Belgium.

The British Journal of Ophthalmology
|February 24, 2017
PubMed
Summary

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Fourier domain-optical coherence tomography (FD-OCT) effectively images the limbus, visualizing the palisades of Vogt and confirming stem cell presence. This technique allows for quantification and may aid in limbal stem cell transplantation.

Area of Science:

  • Ophthalmology
  • Biomedical Imaging
  • Stem Cell Biology

Background:

  • The limbus is crucial for ocular surface maintenance and contains limbal stem cells.
  • Accurate imaging and quantification of limbal structures are vital for understanding ocular health and disease.

Purpose of the Study:

  • To assess Fourier domain-optical coherence tomography (FD-OCT) for imaging and quantifying the palisades of Vogt.
  • To correlate FD-OCT findings with histological data and stem cell markers.

Main Methods:

  • FD-OCT was used to image the limbal regions of 50 healthy volunteers.
  • Image analysis was performed using Matlab software.
  • In vitro immunofluorescent staining of a cadaveric limbus correlated visualized structures with stem cell presence.
Keywords:
CorneaImagingPhysiologyStem Cells

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Main Results:

  • FD-OCT successfully visualized limbal crypts and palisades of Vogt, with fluorescent labeling confirming stem cell presence.
  • Quantification revealed mean palisade ridge width and interpalisade epithelial rete peg width of approximately 72 μm, yielding a palisade density of ~7.4 palisades/mm.
  • Significant differences in these parameters were observed between superior and inferior limbal regions, and influenced by iris color and age.

Conclusions:

  • In vivo FD-OCT is a safe and effective method for imaging the limbus and visualizing the palisades of Vogt.
  • Matlab-based image processing enables quantification and density calculation of limbal palisades.
  • This technique holds potential for improving targeted limbal biopsies for transplantation.