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Retinal nerve fiber layer defect volume deviation analysis using spectral-domain optical coherence tomography.

Joong Won Shin1, Ki Bang Uhm1, Mincheol Seong1

  • 1Department of Ophthalmology, Hanyang University College of Medicine, Seoul, Korea.

Investigative Ophthalmology & Visual Science
|December 11, 2014
PubMed
Summary

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Retinal nerve fiber layer (RNFL) defect volume deviation effectively diagnoses glaucoma and monitors RNFL changes. This method is more sensitive than RNFL defect volume in early glaucoma detection.

Area of Science:

  • Ophthalmology
  • Medical Imaging
  • Glaucoma Research

Background:

  • Glaucoma diagnosis relies on detecting structural and functional changes.
  • Retinal nerve fiber layer (RNFL) thickness maps are crucial for identifying structural damage.

Purpose of the Study:

  • To assess RNFL defect volume deviation based on structural RNFL loss.
  • To compare diagnostic performance of RNFL defect volume and deviation in glaucoma detection.

Main Methods:

  • RNFL defects defined by 20%-70% RNFL loss in thickness maps compared to normative data.
  • RNFL defect volume and deviation calculated by summing pixel volumes and differences.
  • Area under the receiver operating characteristic curves (AUCs) used to evaluate diagnostic ability.
Keywords:
glaucomalost and remaining volumeretinal nerve fiber defectspectral-domain optical coherence tomography

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Main Results:

  • RNFL defect volume deviation (AUC=0.986) and volume (AUC=0.984) showed superior diagnostic ability over circumpapillary RNFL thickness parameters.
  • RNFL defect volume deviation demonstrated better early-stage glaucoma diagnostic performance than RNFL defect volume.
  • Both RNFL defect volume and deviation correlated significantly with visual field mean deviation.

Conclusions:

  • RNFL defect volume deviation is a valuable tool for glaucoma diagnosis and RNFL change monitoring.
  • RNFL defect volume deviation offers higher sensitivity for early glaucoma detection compared to RNFL defect volume.