September 2016
Volume 57, Issue 12
Open Access
ARVO Annual Meeting Abstract  |   September 2016
Segmentation and analysis software for mapping aqueous humor outflow pattern in living mice
Author Affiliations & Notes
  • Dibyendu Mukherjee
    Department of Biomedical Engineering, Duke University, Durham, North Carolina, United States
  • Guorong Li
    Department of Ophthalmology, Duke University Medical Center, Durham, North Carolina, United States
  • W Daniel Stamer
    Department of Ophthalmology, Duke University Medical Center, Durham, North Carolina, United States
  • Sina Farsiu
    Department of Biomedical Engineering, Duke University, Durham, North Carolina, United States
    Department of Ophthalmology, Duke University Medical Center, Durham, North Carolina, United States
  • Footnotes
    Commercial Relationships   Dibyendu Mukherjee, None; Guorong Li, None; W Stamer, None; Sina Farsiu, None
  • Footnotes
    Support  BrightFocus Foundation
Investigative Ophthalmology & Visual Science September 2016, Vol.57, 5936. doi:
  • Views
  • Share
  • Tools
    • Alerts
      ×
      This feature is available to Subscribers Only
      Sign In or Create an Account ×
    • Get Citation

      Dibyendu Mukherjee, Guorong Li, W Daniel Stamer, Sina Farsiu; Segmentation and analysis software for mapping aqueous humor outflow pattern in living mice. Invest. Ophthalmol. Vis. Sci. 2016;57(12):5936.

      Download citation file:


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

      ×
  • Supplements
Abstract

Purpose : To visualize and quantify aqueous humor outflow dynamics at varied levels of intraocular pressure (IOP) in living mice imaged by spectral domain-optical coherence tomography (SD-OCT).

Methods : Conventional outflow tract of four C57 mice were imaged using SD-OCT while holding IOP at 8, 10, 12, 15 or 17 mmHg with a single needle placed in anterior chamber. At each pressure, 5 SD-OCT volumes of conventional outflow tissues, each with 200 B-scans, were captured in 20 min intervals. Speckle variance intensity (SVI) and areas in both Schlemm’s canal (SC) and scleral vessels conducting aqueous humor outflow were visualized and quantified using newly developed image processing algorithms and corresponding software with graphical user interface (GUI) called SchlemmSeg v.1. SchlemmSeg automatically corrects translation, rotation, and scaling to register all B-scans and creates corresponding speckle variance and averaged images. It performs automatic segmentation of all vasculature features and semi-automatic segmentation of SC by utilizing information from temporal mean, speckle variance, and cumulative inter-frame difference images.

Results : The speckle variance areas of SC decreased from 402.7 ± 65.4 µm2 (at 8 mmHg) to 129.3 ± 75 µm2 when IOP held at 17 mmHg. The speckle variance areas of scleral vessels conducting aqueous humor were also IOP-dependent, decreasing from 663.2 ± 111 (at 10 mmHg) to 405 ± 108 µm2 (at 17 mmHg). However, the area was 25.8% smaller at 8 mmHg than that at 10 mmHg. The average SVI in both SC and scleral vessels were similar. In SC, SVI increased by 120%±42% (at 12mmHg), 193.6%±72% (at 15mmHg), and 217.7%±25% (at 17mmHg) relative to values at 10 mmHg, and there was no difference of SVI between 8 and 10 mmHg. A similar pattern of SVI was found in scleral vessels except that there was no increase from 8 to 12 mmHg and ~60% increase of SVI at both 15 and 17 mmHg compared to that at 10 mmHg.

Conclusions : Our data validates SchlemmSeg as the first software capable of mapping and quantifying the aqueous humor outflow in SC and scleral vessels at controlled pressures in living animals. This software is expected to help better understand the aqueous humor outflow dynamic in physiological and glaucoma-related pathological conditions.

This is an abstract that was submitted for the 2016 ARVO Annual Meeting, held in Seattle, Wash., May 1-5, 2016.

 

SchlemmSeg. (1) Data import, automatic segmentation and analysis; (2) manual segmentation; (3) image windows; (4) data export options

SchlemmSeg. (1) Data import, automatic segmentation and analysis; (2) manual segmentation; (3) image windows; (4) data export options

×
×

This PDF is available to Subscribers Only

Sign in or purchase a subscription to access this content. ×

You must be signed into an individual account to use this feature.

×