Investigative Ophthalmology & Visual Science Cover Image for Volume 61, Issue 7
June 2020
Volume 61, Issue 7
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ARVO Annual Meeting Abstract  |   June 2020
A novel automated tool for measuring intraepithelial corneal basal nerves in murine models of aging, wound-healing and limbal stem cell deficiency
Author Affiliations & Notes
  • Nick Di Girolamo
    Medical Sciences, University of New South Wales, Sydney, New South Wales, Australia
  • Hugh Tuck
    Medical Sciences, University of New South Wales, Sydney, New South Wales, Australia
  • Mijeong Park
    Medical Sciences, University of New South Wales, Sydney, New South Wales, Australia
  • Alexander Richardson
    Medical Sciences, University of New South Wales, Sydney, New South Wales, Australia
  • Joshua Machet
    Medical Sciences, University of New South Wales, Sydney, New South Wales, Australia
  • Michael Carnell
    Medical Sciences, University of New South Wales, Sydney, New South Wales, Australia
  • Footnotes
    Commercial Relationships   Nick Di Girolamo, None; Hugh Tuck, None; Mijeong Park, None; Alexander Richardson, None; Joshua Machet, None; Michael Carnell, None
  • Footnotes
    Support  NHMRC APP1101078 and APP1156944, ARC SR1101002
Investigative Ophthalmology & Visual Science June 2020, Vol.61, 1428. doi:
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    • Get Citation

      Nick Di Girolamo, Hugh Tuck, Mijeong Park, Alexander Richardson, Joshua Machet, Michael Carnell; A novel automated tool for measuring intraepithelial corneal basal nerves in murine models of aging, wound-healing and limbal stem cell deficiency. Invest. Ophthalmol. Vis. Sci. 2020;61(7):1428.

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      © ARVO (1962-2015); The Authors (2016-present)

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Abstract

Purpose : Intraepithelial corneal basal nerves (ICBNs) are captured by in vivo confocal microscopy; however, this mode of visualization lacks resolution. Corneas, immunostained and imaged ex vivo solve this problem, however comprehensive analyses of nerve parameters is sub-optimal. This study compared current methods of analyzing intraepithelial ICBNs to a new noise-based segmentation (NoBS) approach in mouse models of aging (n=49), wound-healing (n=32), and limbal stem cell deficiency (n=32).

Methods : For aging, eyes were collected from 2-52 week-old normal C57BL/6 mice (n≥4/time-point). For wound-healing and limbal stem cell deficiency, 7 week-old mice received a limbal-sparing or limbal-to-limbal epithelial debridement to their right cornea, respectively. Eyes were collected 2-16 weeks post-injury (n=4/group/time-point), corneas procured, immunolabelled with βIII-tubulin, flat-mounted and imaged by scanning confocal microscopy.

Results : A subset of images (n=15) from each model was analyzed for ICBN density using various analytical platforms, and an agreement to manual-tracing (gold-standard) was established for all methods. NoBS had the strongest Pearson’s correlation (r=0.97), followed by manual-counting (r=0.93), manual-thresholding (r=0.89), Imaris-bitplane (r=0.57) and automated-thresholding with ImageJ (r=0.18). NoBS was used to compute all measurements as percentage (%) area occupied by nerves. Between 3-12 weeks of age, ICBN density increased from 5.4% to 17.8% centrally (p<0.01) and 13.0% to 24.9% peripherally (p<0.01), then by 20-weeks (and beyond) decreased to 10.5% centrally (p<0.01) and 18.3% peripherally (p<0.01). During wound-healing, ICBN density was gradually restored, and at 8-weeks reached control levels in the centre (p>0.1) and periphery (p>0.1) but failed to reform the central whorl even after 16-weeks. In limbal stem cell deficient mice, ICBNs regeneration was observed over time and was not statistically different to controls in the centre or periphery at 16-weeks (p>0.1), however the curvilinear pattern that characterizes ICBNs in normal corneas, was not restored.

Conclusions : Our new analytical modality affords the potential to rapidly and reliably detect microstructural changes to ICBNs. This will enable the refinement of non-invasive diagnostic and surveillance tests for patients with ocular and/or systemic diseases.

This is a 2020 ARVO Annual Meeting abstract.

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