Abstract
Purpose :
The direct, non-invasive measurement of ocular rigidity can be achieved using a validated method based on dynamic OCT imaging and IOP measurements. Recent improvements have been made by employing a neural network approach to segment the choroid. The objective of this study is to assess the repeatability of pulsatile volume change (ΔV) and ocular rigidity (OR) measurements using this approach in living eyes from children and young adults.
Methods :
OR is measured using Friedenwald’s equation, where the pulsatile ocular volume change is obtained from dynamic OCT imaging of the choroid, and the pulsatile intraocular pressure change is obtained using dynamic tonometry. A neural network for choroid segmentation was trained on 10,798 manually segmented static OCT scans to an accuracy of 99.25% and loss of 0.023. The network was then adapted for use in OCT scans acquired in time series. The method’s repeatability was assessed using the Bland-Altman plot and the Intraclass correlation coefficient (ICC).
Results :
Seventeen subjects (17 eyes; 5 males) aged 6 to 25 years were enrolled. Repeatability was assessed for two consecutive measurements of ΔV and OR. Repeated measures were not statistically different (p > 0.05). The Bland-Altman plot, as well as the ICC showed good agreement between intra-session measurements of ΔV and OR. The single and average measures ICC for ΔV was 0.910 and 0.953 respectively. The single and average measures ICC for OR was 0.808 and 0.894 respectively.
Conclusions :
We hereby demonstrate the repeatability of ΔV and OR using a non-invasive measurement method utilizing a neural network approach in children and young adults. This study confirms good repeatability for further clinical studies on ocular rigidity in these populations.
This abstract was presented at the 2024 ARVO Annual Meeting, held in Seattle, WA, May 5-9, 2024.