June 2021
Volume 62, Issue 8
Open Access
ARVO Annual Meeting Abstract  |   June 2021
Ultrasound biomicroscopy image analysis technique for the human iris
Author Affiliations & Notes
  • Trisha Miglani
    University of Maryland School of Medicine, Baltimore, Maryland, United States
  • Michael Chang
    University of Maryland School of Medicine, Baltimore, Maryland, United States
  • Moran Roni Levin
    University of Maryland School of Medicine, Baltimore, Maryland, United States
  • Janet Leath Alexander
    University of Maryland School of Medicine, Baltimore, Maryland, United States
  • Footnotes
    Commercial Relationships   Trisha Miglani, None; Michael Chang, None; Moran Levin, None; Janet Alexander, None
  • Footnotes
    Support  Program for Research Initiated by Students and Mentors (PRISM) for UM Medical Students
Investigative Ophthalmology & Visual Science June 2021, Vol.62, 387. doi:
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    • Get Citation

      Trisha Miglani, Michael Chang, Moran Roni Levin, Janet Leath Alexander; Ultrasound biomicroscopy image analysis technique for the human iris. Invest. Ophthalmol. Vis. Sci. 2021;62(8):387.

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

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Abstract

Purpose : The iris is a highly clinically relevant structure, but most literature on iris pathology is limited to qualitative observations. In this study, we aim to develop novel quantitative assessment tools for evaluation of the iris. We have developed a standardized measurement protocol of iris parameters with reliability analysis using ultrasound biomicroscopy (UBM) and ImageJ software to establish the rigor and reproducibility of these measurements and provide a quantitative description of the human iris in subjects from infancy to young adulthood.

Methods : 14 pediatric control subjects comprising of 25 total eyes (mean age 1.96yrs, standard deviation 1.18yrs, and median age 1.81yrs) were recruited prospectively and underwent UBM imaging. Two observers measured 19 structural iris parameters on four UBM image types per eye using ImageJ. Each image was analyzed by both observers using two methods: Standard and Edge Finder, which uses an edge detector to delineate tissue borders based on changes in intensity. Reliability analysis was comprised of intra-observer repeatability (IOR) and inter-observer agreement (IOA). IOR was determined by calculating the coefficient of variation (CV) and correlation coefficient (r) for each parameter, and IOA was assessed by determining the intra-class correlation coefficient (ICC) for each parameter.

Results : Axial image types resulted in superior ICC, CV and r values for the majority of parameters with the use of an edge finder tool. Longitudinal image types resulted in superior ICC, CV and r values for the majority of parameters using the standard method of image analysis on the raw image.

Conclusions : The use of an edge finder tool increased measurement reliability in axial image types, but it did not increase reliability in longitudinal images.

This is a 2021 ARVO Annual Meeting abstract.

 

Table 1: Reliability analysis results of standard and edge finder methods on axial and longitudinal ultrasound biomicroscopy (UBM) images

Table 1: Reliability analysis results of standard and edge finder methods on axial and longitudinal ultrasound biomicroscopy (UBM) images

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