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

PURPOSE

To report the retinal nerve fiber layer (RNFL) defect volume deviation according to structural RNFL loss in RNFL thickness maps.

METHODS

Retinal nerve fiber layer defect is defined in RNFL thickness maps by the degree of RNFL loss. A 20% to 70% degree of RNFL loss was set with a 1% interval as the reference level for determining the boundary of RNFL defects. Each individual RNFL thickness map was compared with a normative database map and the region below the reference level was identified as an RNFL defect. The RNFL defect volume was calculated by summing the volumes of each pixel inside RNFL defect. The RNFL defect volume deviation was calculated by summing the differences between the normative database and the subject's RNFL measurements. To evaluate the glaucoma diagnostic ability, the areas under the receiver operating characteristics curves (AUCs) were calculated.

RESULTS

Retinal nerve fiber layer defect volume and RNFL defect volume deviation (0.984 and 0.986, respectively) had significantly greater AUCs than all circumpapillary RNFL thickness parameters (all P < 0.001). In the early stage of RNFL loss (under 31% loss of RNFL), RNFL defect volume deviation showed better diagnostic performance than the RNFL defect volume. In multivariate analysis, RNFL defect volume and RNFL defect volume deviation were significantly associated with the mean deviation in visual field tests.

CONCLUSIONS

Retinal nerve fiber layer defect volume deviation is a useful tool for diagnosing glaucoma and monitoring RNFL change. In early stage of RNFL loss, RNFL defect volume deviation is more sensitive for detecting glaucoma than the RNFL defect volume measurements.