論文

査読有り 本文へのリンクあり
2021年12月

Association between visual field damage and corneal structural parameters

Scientific Reports
  • Alexandru Lavric
  • ,
  • Valentin Popa
  • ,
  • Hidenori Takahashi
  • ,
  • Rossen M. Hazarbassanov
  • ,
  • Siamak Yousefi

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記述言語
英語
掲載種別
研究論文(学術雑誌)
DOI
10.1038/s41598-021-90298-0
出版者・発行元
Springer Science and Business Media LLC

Abstract

The main goal of this study is to identify the association between corneal shape, elevation, and thickness parameters and visual field damage using machine learning. A total of 676 eyes from 568 patients from the Jichi Medical University in Japan were included in this study. Corneal topography, pachymetry, and elevation images were obtained using anterior segment optical coherence tomography (OCT) and visual field tests were collected using standard automated perimetry with 24-2 Swedish Interactive Threshold Algorithm. The association between corneal structural parameters and visual field damage was investigated using machine learning and evaluated through tenfold cross-validation of the area under the receiver operating characteristic curves (AUC). The average mean deviation was − 8.0 dB and the average central corneal thickness (CCT) was 513.1 µm. Using ensemble machine learning bagged trees classifiers, we detected visual field abnormality from corneal parameters with an AUC of 0.83. Using a tree-based machine learning classifier, we detected four visual field severity levels from corneal parameters with an AUC of 0.74. Although CCT and corneal hysteresis have long been accepted as predictors of glaucoma development and future visual field loss, corneal shape and elevation parameters may also predict glaucoma-induced visual functional loss.

リンク情報
DOI
https://doi.org/10.1038/s41598-021-90298-0 本文へのリンクあり
URL
http://www.nature.com/articles/s41598-021-90298-0.pdf
URL
http://www.nature.com/articles/s41598-021-90298-0
ID情報
  • DOI : 10.1038/s41598-021-90298-0
  • eISSN : 2045-2322

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