June 2017
Volume 58, Issue 8
Open Access
ARVO Annual Meeting Abstract  |   June 2017
Novel ImageJ Analysis Technique for the Quantitation of Apoptotic Hotspots
Author Affiliations & Notes
  • Tyler Nicholas Heisler-Taylor
    Havener Eye Institute, Ophthalmology and Visual Science, The Ohio State University, Columbus, Ohio, United States
    Department of Biomedical Engineering, The Ohio State University, Columbus, Ohio, United States
  • Anchshana Haridas
    Havener Eye Institute, Ophthalmology and Visual Science, The Ohio State University, Columbus, Ohio, United States
  • Bongsu Kim
    Havener Eye Institute, Ophthalmology and Visual Science, The Ohio State University, Columbus, Ohio, United States
  • Rania Kusibati
    Havener Eye Institute, Ophthalmology and Visual Science, The Ohio State University, Columbus, Ohio, United States
  • Colleen M Cebulla
    Havener Eye Institute, Ophthalmology and Visual Science, The Ohio State University, Columbus, Ohio, United States
  • Footnotes
    Commercial Relationships   Tyler Heisler-Taylor, None; Anchshana Haridas, None; Bongsu Kim, None; Rania Kusibati, None; Colleen Cebulla, None
  • Footnotes
    Support  NIH K08EY022672, P30 CA016058 ( OSU-CCC Nucleic Acids Shared Resource), NCATS KL2TR001068. The content is solely the responsibility of the authors and does not necessarily represent the official views of the funding institutions. Additional funds were provided by the Ohio Lions Eye Research Foundation, Ophthalmology Fund #313310, and the Patti Blow Fund
Investigative Ophthalmology & Visual Science June 2017, Vol.58, 667. doi:
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    • Get Citation

      Tyler Nicholas Heisler-Taylor, Anchshana Haridas, Bongsu Kim, Rania Kusibati, Colleen M Cebulla; Novel ImageJ Analysis Technique for the Quantitation of Apoptotic Hotspots. Invest. Ophthalmol. Vis. Sci. 2017;58(8):667.

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

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Abstract

Purpose : To present a novel, semi-automated method to quantitate TUNEL-positive cells in high intensity ‘hotspot’ regions within retinal cross sections. Previously established automated methods have not been able to sufficiently measure these high intensity or saturated regions.

Methods : Retinal detachments (RD) were induced in murine eyes with subretinal hyaluronic acid injection under an IACUC-approved protocol. Mice were sacrificed at day 3 and the eyes were harvested and enucleated for IHC staining. For apoptosis quantification in retinal frozen sections, fluorescence images of TUNEL-positive retinal cells (568nm) and DAPI nuclear labeling (461nm) in detached or corresponding control areas were taken with a 20x objective lens with identical illumination and exposure times. Images were then analyzed and compared with two techniques: 1) the RETINA Analysis Toolkit macro for ImageJ and 2) a semi-automatic multichannel color thresholding technique. The multichannel thresholding utilizes the color threshold technique in ImageJ by thresholding the RGB channels allowing for the selection of both DAPI and TUNEL positive cell nuclei simultaneously. Student’s t-test was used for statistical analysis.

Results : Analysis of the ratio of TUNEL-positive cells captured by the Toolkit macro over those captured through multichannel thresholding in TUNEL ‘hotspot’ regions resulted in a significant difference (0.678 ± 0.229 macro/multi ratio vs. 1.0 ± 0.0 multi/multi ratio, p = 0.0183) while ‘normal’ TUNEL regions were indistinguishable (1.048 ± 0.532 macro/multi vs. 1.0 ± 0.0 multi/multi, p = 0.8340).

Conclusions : The method presented above to analyze regions of intense apoptosis has significantly improved accuracy compared to previously established automated systems by also accounting for the nuclear stain when counting apoptotic cells. Incorporating this new technique as an option within the analysis macro would facilitate analysis of nuclear hotspot regions.

This is an abstract that was submitted for the 2017 ARVO Annual Meeting, held in Baltimore, MD, May 7-11, 2017.

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