JMIR Publications

ABSTRACT

Background:

It has been a clinical emphasis and challenge to detect glaucoma in highly myopic eyes. Due to the axial elongation-associated changes in the optic nerve and retina in high myopia, traditional methods like optic disc evaluation and visual field were not able to correctly differentiate the glaucomatous lesions.

Objective:

To develop a neural network for adjusting the dependence of the peripapillary retinal nerve fiber layer (RNFL) thickness (RNFLT) profile on age, gender and ocular biometric parameters, and to evaluate its performance in glaucoma diagnosis, especially in high myopia.

Methods:

RNFLT with 768 points at the circumferential 3.4 mm scan was measured using spectral-domain optical coherence tomography (OCT). A fully connected network and a radial basis function network were trained for vertical (scaling) and horizontal (shift) transformation of the RNFLT profile with adjustment for age, axial length (AL), disc-fovea angle and distance, in a test group of 2223 non-glaucomatous eyes. The performance of RNFLT compensation was evaluated in an independent group of 254 glaucoma patients and 254 non-glaucomatous participants.

Results:

By applying the RNFL compensation algorithm, the area under the receiver operating characteristic curve in detecting glaucoma increased from 0.70 to 0.84, from 0.75 to 0.89, from 0.77 to 0.89, and from 0.78 to 0.87, for eyes in the highest 10% (mean: 26.0±0.9mm), 20% (25.3±1.0mm), and highest 30% (24.9±1.0mm) percentile subgroup of the AL distribution, and in eyes of any AL (23.5±1.2mm), in comparing with unadjusted RNFLT, respectively. The difference between uncompensated versus compensated RNFLT values increased with longer axial length, with enlargement of 19.8%, 18.9%, 16.2% and 11.3% in the highest 10%, 20% and 30% percentile subgroups, and in all eyes, respectively.

Conclusions:

In a population-based study sample, an algorithm-based adjustment for age, gender and ocular biometric parameters improved the diagnostic precision of the RNFLT profile for glaucoma detection in particular in myopic and highly myopic eyes.