June 2023
Volume 64, Issue 9
Open Access
ARVO Imaging in the Eye Conference Abstract  |   June 2023
Remote Quantification of Ocular Surface Epitheliopathy Using a Standardized System: A large-scale feasibility validation
Author Affiliations & Notes
  • Matteo Tomasi
    Boston Eye Diagnostics, Boston, Massachusetts, United States
  • Francisco Amparo
    Universidad de Monterrey, Mexico
  • Juan Carlos Ochoa Tabares
    Cornea Atencion Especializada, Mexico
  • Reza Dana
    Massachusetts Eye and Ear, Boston, Massachusetts, United States
  • Footnotes
    Commercial Relationships   Matteo Tomasi, Boston Eye Diagnostics Inc. (I); Francisco Amparo, Boston Eye Diagnostics Inc. (I); Juan Carlos Ochoa Tabares, None; Reza Dana, Boston Eye Diagnostics Inc. (I)
  • Footnotes
    Support  None
Investigative Ophthalmology & Visual Science June 2023, Vol.64, PB008. doi:
  • Views
  • Share
  • Tools
    • Alerts
      ×
      This feature is available to authenticated users only.
      Sign In or Create an Account ×
    • Get Citation

      Matteo Tomasi, Francisco Amparo, Juan Carlos Ochoa Tabares, Reza Dana; Remote Quantification of Ocular Surface Epitheliopathy Using a Standardized System: A large-scale feasibility validation. Invest. Ophthalmol. Vis. Sci. 2023;64(9):PB008.

      Download citation file:


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

      ×
  • Supplements
Abstract

Purpose : Although many automated methods are available for quantitative and standardized assessment of ocular pathology, the ocular surface space significantly lacks such valuable tools.
We report the application of a new system that measures corneal and conjunctival fluorescein-positive epitheliopathy through a computer-assisted imaging and processing algorithm. The system is based on a modular hardware package and a processing platform to consistently acquire data for objective quantification of ocular surface disease clinical signs. We deployed the system in clinics more than 2,500 miles apart demonstrating its feasibility and compatibility with large-scale clinical applications.

Methods : We shipped and remotely guided the setup of the ocular surface evaluation system in multiple ophthalmology clinics. Users received a brief training session (~ 90 min) to cover the installation and application of the technology. We included non-randomized patients with various ocular surface conditions and clinically-confirmed corneal or conjunctival epitheliopathy. For each of the ocular surface scans, the quality and consistency of the data were evaluated to confirm feasibility in mass-screening projects, large clinical trials, and routine clinical visits.

Results : We deployed a total of 60 systems in clinics across North America and obtained more than 2,000 patient scans. A total of 70 users participated, and 100% were able to perform scans on regular patients. The system successfully transmitted the clinical data through secure HIPAA connections for its central evaluation and processing. In 97% of the cases, the system confirmed the presence of clinically diagnosed epitheliopathy and, most importantly, quantified the epithelial staining areas with high levels of correlation with the clinical evaluation (r=0.81, p <0.01) (currently analyzed data subset).

Conclusions : We demonstrated that the evaluated system provides consistent objective evaluation and quantification of corneal epithelial disease without human input during the grading process, increasing the repeatability and reducing evaluation times compared with traditional imaging techniques. We showed feasibility and scalability to cover large numbers of clinics despite geographical barriers. The proposed tool is promising for objective, repeatable, and systematic evaluation of ocular surface epitheliopathy across large populations.

This abstract was presented at the 2023 ARVO Imaging in the Eye Conference, held in New Orleans, LA, April 21-22, 2023.

×
×

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.

×