June 2013
Volume 54, Issue 15
Free
ARVO Annual Meeting Abstract  |   June 2013
Imaging retinal nerve fiber loss in glaucoma using adaptive optics scanning laser ophthalmoscopy
Author Affiliations & Notes
  • Gang Huang
    Optometry School, Indiana University, Bloomington, IN
  • Thomas Gast
    Optometry School, Indiana University, Bloomington, IN
  • Ting Luo
    Optometry School, Indiana University, Bloomington, IN
  • Toco Chui
    Optometry School, Indiana University, Bloomington, IN
  • William Swanson
    Optometry School, Indiana University, Bloomington, IN
  • Victor Malinovsky
    Optometry School, Indiana University, Bloomington, IN
  • Stephen Burns
    Optometry School, Indiana University, Bloomington, IN
  • Footnotes
    Commercial Relationships Gang Huang, None; Thomas Gast, None; Ting Luo, None; Toco Chui, None; William Swanson, None; Victor Malinovsky, None; Stephen Burns, None
  • Footnotes
    Support None
Investigative Ophthalmology & Visual Science June 2013, Vol.54, 1451. doi:
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    • Get Citation

      Gang Huang, Thomas Gast, Ting Luo, Toco Chui, William Swanson, Victor Malinovsky, Stephen Burns; Imaging retinal nerve fiber loss in glaucoma using adaptive optics scanning laser ophthalmoscopy. Invest. Ophthalmol. Vis. Sci. 2013;54(15):1451.

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

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Abstract
 
Purpose
 

To investigate structural differences in the retinal nerve fiber layer (RNFL) along a vertical path across the temporal raphe of healthy and glaucomatous eyes using adaptive optics(AO) imaging. To relate the AO RNFL montages to optical coherence tomography (OCT, Spectralis, Heidelberg Engineering) and visual field measurements.

 
Methods
 

One eye was imaged for 6 patients with glaucoma and 4 control subjects of a similar age. Patients with glaucoma were selected from a larger study based on the presence of asymmetric damage to nasal visual field. All subjects passed complete ophthalmic examinations and had recent reliable visual fields. A 10° vertical by 3° horizontal degree region centered 10° temporally from the fovea was imaged by a steerable AO-SLO system. A RNFL montage was built up from the individual AOSLO images. A 20° by 10° region centered 10° temporally from the fovea was imaged by OCT with the B-scans oriented vertically. The RNFL thickness was manually measured on the OCT images.

 
Results
 

Consistent with our previous work (Huang et al., Optometry Vision Sci, 2012), the fiber bundles in control subjects were highly-reflective and showed high contrast between individual bundles. In contrast, all glaucomatous eyes showed absence of fiber bundles across the raphe. The extent of the bundle absence was qualitatively consistent with the local visual field loss. Complete absence of the bundles was observed in areas corresponding to areas of visual field depression of more than 5 dB. For regions of less field depression, bundles could be observed but appeared less crisp and the boundaries between individual bundles were less defined. The RNFL thickness measurements by OCT also reflected vertical asymmetries in RNFL, consistent with the results above.

 
Conclusions
 

The high-resolution and contrast available from the AOSLO images allowed detailed visualization of the RNFL and the impact of modest perimetric defects on the NFL appearance. The structural loss in RNFL is qualitatively in agreement with the local visual field loss and the RNFL thickness difference. The AOSLO can serve as a tool to investigate the RNFL in glaucoma.

 
 
Figure 1. The RNFL differences are shown in two RNFL montages centered 10° temporally from the fovea . The left is from a control subject and the other is from a patient who has a field depression of -2 dB on the superior and -13 dB on the inferior side.
 
Figure 1. The RNFL differences are shown in two RNFL montages centered 10° temporally from the fovea . The left is from a control subject and the other is from a patient who has a field depression of -2 dB on the superior and -13 dB on the inferior side.
 
Keywords: 629 optic nerve • 550 imaging/image analysis: clinical • 758 visual fields  
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