Two-photon imaging microscopy of non-stained human epiretinal membranes

Juan M Bueno1, Xavier Valldeperas2

  • 1Laboratorio de Óptica, Instituto Universitario de Investigación en Óptica y Nanofísica, Campus de Espinardo (Ed. 34), CEIR Campus Mare Nostrum (CMN), Universidad de Murcia, 30100 Murcia, Spain.

Insights

Two-photon imaging microscopy differentiates epiretinal membranes (ERMs) based on origin. This technique quantifies differences between idiopathic (iERM) and non-idiopathic (non-iERM) ERMs using autofluorescence and collagen signals.

Area of Science:

  • Ophthalmology
  • Biomedical Imaging
  • Cell Biology

Background:

  • Epiretinal membranes (ERMs) are cellular and extracellular matrix formations.
  • ERMs are classified as idiopathic (iERM) or non-idiopathic (non-iERM), with distinct origins.
  • Current visualization methods for ERMs are time-consuming and primarily qualitative.

Purpose of the Study:

  • To explore and quantify differences between non-stained human iERM and non-iERM.
  • To assess the potential of two-photon imaging microscopy for objective ERM characterization.
  • To differentiate ERM types based on their genesis using advanced imaging techniques.

Main Methods:

  • Utilized two-photon excitation fluorescence (TPEF) and second harmonic generation (SHG) signals.
  • Applied TPEF-SHG imaging to non-stained human ERM samples.
  • Developed a quantitative index from TPEF-SHG image pairs and analyzed collagen spatial arrangement.

Main Results:

  • Established an index to differentiate between iERM and non-iERM based on TPEF-SHG signals.
  • Quantified differences in collagen-based tissue spatial arrangement between ERM types.
  • Demonstrated the potential of label-free two-photon imaging for ERM characterization.

Conclusions:

  • Two-photon imaging microscopy, combining TPEF and SHG, offers an objective method to differentiate ERM types.
  • The developed index and collagen analysis provide quantitative insights into ERM composition and origin.
  • This technique may improve the understanding and diagnosis of ERM-related conditions.

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