Semi-Automated Analysis of Foveal Maturity in Premature and Full-Term Infants Using Handheld Swept-Source Optical Coherence Tomography.

Journal: Translational Vision Science & Technology
Published:
Abstract

Purpose: To develop a semi-automated method of measuring foveal maturity using investigational handheld swept source-optical coherence tomography (SS-OCT).

Methods: In this prospective, observational study, full-term newborns and preterm infants undergoing routine retinopathy of prematurity screening were imaged. Semi-automated analysis measured foveal angle and chorioretinal thicknesses at the central fovea and average two-sided parafovea by three-grader consensus, correlating with OCT features and demographics.

Results: One hundred ninety-four imaging sessions from 70 infants were included (47.8% girls, 37.6 ± 3.4 weeks postmenstrual age, 26 preterm infants with birth weight 1057 ± 325.0, gestational age 29.0 ± 3.0 weeks). Foveal angle (96.1 ± 22.0 degrees) steepened with increasing birth weight (P = 0.003), decreasing inner retinal layer thickness, and increasing gestational age, postmenstrual age, and foveal and parafoveal choroidal thickness (all P < 0.001). Inner retinal fovea/parafovea ratio (0.4 ± 0.2) correlated with increasing inner foveal layers, decreasing postmenstrual age, gestational age, and birth weight (all P < 0.001). Outer retinal F/P ratio (0.7 ± 0.2) correlated with ellipsoid zone presence (P < 0.001), increased gestational age (P = 0.002), and birth weight (P = 0.003). Foveal (447.8 ± 120.6 microns) and parafoveal (420.9 ± 109.2) choroidal thicknesses correlated with foveal ellipsoid zone presence (P = 0.007 and P = 0.01, respectively), postmenstrual age, birth weight, gestational age, and decreasing inner retinal layers (all P < 0.001).

Conclusions: Foveal development is dynamic and partially observed through semi-automated analysis of handheld SS-OCT imaging. Translational relevance: Semi-automated analysis of SS-OCT images can identify measures of foveal maturity.

Authors
Sumner Lawson, Emily Tam, Yujiao Zheng, Teng Liu, Tatiana Monger, Karen Lee, Alex Legocki, John Kelly, Leona Ding, Ruikang Wang, Kristina Tarczy Hornoch, Michelle Cabrera
Relevant Conditions

Premature Infant