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

PURPOSE: Intrachoroidal cavitations (ICCs) are peripapillary pathological lesions generally 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 coher...

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Autores principales: Fujimoto, Satoko, Miki, Atsuya, Maruyama, Kazuichi, Mei, Song, Mao, Zaixing, Wang, Zhenguo, Chan, Kinpui, Nishida, Kohji
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Association for Research in Vision and Ophthalmology 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9279919/
https://www.ncbi.nlm.nih.gov/pubmed/35802370
http://dx.doi.org/10.1167/tvst.11.7.1
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author Fujimoto, Satoko
Miki, Atsuya
Maruyama, Kazuichi
Mei, Song
Mao, Zaixing
Wang, Zhenguo
Chan, Kinpui
Nishida, Kohji
author_facet Fujimoto, Satoko
Miki, Atsuya
Maruyama, Kazuichi
Mei, Song
Mao, Zaixing
Wang, Zhenguo
Chan, Kinpui
Nishida, Kohji
author_sort Fujimoto, Satoko
collection PubMed
description PURPOSE: Intrachoroidal cavitations (ICCs) are peripapillary pathological lesions generally 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.
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spelling pubmed-92799192022-07-15 Three-Dimensional Volume Calculation of Intrachoroidal Cavitation Using Deep-Learning–Based Noise Reduction of Optical Coherence Tomography Fujimoto, Satoko Miki, Atsuya Maruyama, Kazuichi Mei, Song Mao, Zaixing Wang, Zhenguo Chan, Kinpui Nishida, Kohji Transl Vis Sci Technol Retina PURPOSE: Intrachoroidal cavitations (ICCs) are peripapillary pathological lesions generally 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. The Association for Research in Vision and Ophthalmology 2022-07-08 /pmc/articles/PMC9279919/ /pubmed/35802370 http://dx.doi.org/10.1167/tvst.11.7.1 Text en Copyright 2022 The Authors https://creativecommons.org/licenses/by-nc-nd/4.0/This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
spellingShingle Retina
Fujimoto, Satoko
Miki, Atsuya
Maruyama, Kazuichi
Mei, Song
Mao, Zaixing
Wang, Zhenguo
Chan, Kinpui
Nishida, Kohji
Three-Dimensional Volume Calculation of Intrachoroidal Cavitation Using Deep-Learning–Based Noise Reduction of Optical Coherence Tomography
title Three-Dimensional Volume Calculation of Intrachoroidal Cavitation Using Deep-Learning–Based Noise Reduction of Optical Coherence Tomography
title_full Three-Dimensional Volume Calculation of Intrachoroidal Cavitation Using Deep-Learning–Based Noise Reduction of Optical Coherence Tomography
title_fullStr Three-Dimensional Volume Calculation of Intrachoroidal Cavitation Using Deep-Learning–Based Noise Reduction of Optical Coherence Tomography
title_full_unstemmed Three-Dimensional Volume Calculation of Intrachoroidal Cavitation Using Deep-Learning–Based Noise Reduction of Optical Coherence Tomography
title_short Three-Dimensional Volume Calculation of Intrachoroidal Cavitation Using Deep-Learning–Based Noise Reduction of Optical Coherence Tomography
title_sort three-dimensional volume calculation of intrachoroidal cavitation using deep-learning–based noise reduction of optical coherence tomography
topic Retina
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9279919/
https://www.ncbi.nlm.nih.gov/pubmed/35802370
http://dx.doi.org/10.1167/tvst.11.7.1
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