Novel use of 3T MRI in assessment of optic nerve volume in glaucoma

  • Norlina M. Ramli
  • Sabrilhakim Sidek
  • Fadzlina A. Rahman
  • Mohammadreza Peyman
  • Mimiwati Zahari
  • Kartini Rahmat
  • Norlisah Ramli
Glaucoma

Abstract

Purpose

To measure optic nerve (ON) volume using 3 T magnetic resonance imaging (MRI), to correlate ON volume with retinal nerve fiber layer (RNFL) thickness, and to determine the viability of MRI as an objective tool in distinguishing glaucoma severity.

Methods

In this cross-sectional study, 30 severe glaucoma patients, 30 mild glaucoma patients and 30 age-matched controls were recruited. All subjects underwent standard automated perimetry, RNFL analysis and 3 T MRI examinations. Glaucoma patients were classified according to the Hodapp–Anderson–Parish classification. Pearson’s correlation coefficient was used to correlate ON volume with RNFL, and receiver operating curve (ROC) analysis was performed to determine the sensitivity and specificity of ON volume in detecting glaucoma severity.

Results

Optic nerve volume was significantly lower in both the left and right eyes of the severe glaucoma group (168.70 ± 46.28 mm3; 167.40 ± 45.36 mm3) than in the mild glaucoma group (264.03 ± 78.53 mm3; 264.76 ± 78.88 mm3) and the control group (297.80 ± 71.45 mm3; 296.56 ± 71.02 mm3). Moderate correlation was observed between: RNFL thickness and ON volume (r = 0.51, p <0.001), and in mean deviation of visual field and optic nerve volume (r = 0.60, p < 0.001). ON volume below 236 mm3 was 96 % sensitive and 80 % specific for the detection of severe glaucoma.

Conclusions

MRI measured optic nerve volume is a reliable method of assessing glaucomatous damage beyond the optic nerve head. A value of 236 mm3 and below can be used to define severe glaucoma.

Keywords

Glaucoma MRI Optic nerve volume Retinal nerve fiber layer thickness 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2014

Authors and Affiliations

  • Norlina M. Ramli
    • 1
  • Sabrilhakim Sidek
    • 2
    • 3
  • Fadzlina A. Rahman
    • 1
  • Mohammadreza Peyman
    • 1
  • Mimiwati Zahari
    • 1
  • Kartini Rahmat
    • 2
  • Norlisah Ramli
    • 2
  1. 1.Department of OphthalmologyUniversity of Malaya Eye Research Centre, University MalayaKuala LumpurMalaysia
  2. 2.Department of Biomedical ImagingUniversity Malaya Research Imaging CentreKuala LumpurMalaysia
  3. 3.Medical Imaging Unit, Faculty of MedicineUniversiti Teknologi MARASelangorMalaysia

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