Three-Dimensional Volume Calculation of Intrachoroidal Cavitation Using Deep-Learning–Based Noise Reduction of Optical Coherence Tomography

Abstract

Purpose: Intrachoroidal cavitations (ICCs) are peripapillary pathological lesions gener-ally associated with high myopia that can cause visual field (VF) defects. The current study aimed to evaluate a three-dimensional (3D) volume parameter of ICCs segmented from volumetric swept-source optical coherence tomography (SS-OCT) images processed using deep learning (DL)-based noise reduction and to investigate its correlation with VF sensitivity. Methods: Thirteen eyes of 12 consecutive patients with peripapillary ICCs were enrolled. DL-based denoising and further analyses were applied to parapapillary 6 × 6-mm volumetric SS-OCT scans. Then, 3D ICC volume and two-dimensional depth and length measurements of the ICCs were calculated. The correlations between ICC parameters and VF sensitivity were investigated. Results: The ICCs were located in the inferior hemiretina in all eyes. ICC volume (P = 0.02; regression coefficient [RC], −0.007) and ICC length (P = 0.04; RC, −4.51) were negatively correlated with the VF mean deviation, whereas ICC depth (P = 0.15) was not. All of the parameters, including ICC volume (P = 0.01; RC, −0.004), ICC depth (P = 0.02; RC, −0.008), and ICC length (P = 0.045; RC, −2.11), were negatively correlated with the superior mean total deviation. Conclusions: We established the volume of ICCs as a new 3D parameter, and it reflected their influence on visual function. The automatic delineation and 3D rendering may lead to improved detection and pathological understanding of ICCs. Translational Relevance: This study demonstrated the correlation between the 3D volume of ICCs and VF sensitivity.