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Artificial Intelligence-Based Quantification of Central Macular Fluid Volume and VA Prediction for Diabetic Macular Edema Using OCT Images

INTRODUCTION: We studied the correlation of central macular fluid volume (CMFV) and central subfield thickness (CST) with best-corrected visual acuity (BCVA) in treatment-naïve eyes with diabetic macular edema (DME) 1 month after anti-vascular endothelial growth factor (VEGF) therapy. METHODS: This...

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Autores principales: Ye, Xin, Gao, Kun, He, Shucheng, Zhong, Xiaxing, Shen, Yingjiao, Wang, Yaqi, Shao, Hang, Shen, Lijun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Healthcare 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10441848/
https://www.ncbi.nlm.nih.gov/pubmed/37318706
http://dx.doi.org/10.1007/s40123-023-00746-5
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author Ye, Xin
Gao, Kun
He, Shucheng
Zhong, Xiaxing
Shen, Yingjiao
Wang, Yaqi
Shao, Hang
Shen, Lijun
author_facet Ye, Xin
Gao, Kun
He, Shucheng
Zhong, Xiaxing
Shen, Yingjiao
Wang, Yaqi
Shao, Hang
Shen, Lijun
author_sort Ye, Xin
collection PubMed
description INTRODUCTION: We studied the correlation of central macular fluid volume (CMFV) and central subfield thickness (CST) with best-corrected visual acuity (BCVA) in treatment-naïve eyes with diabetic macular edema (DME) 1 month after anti-vascular endothelial growth factor (VEGF) therapy. METHODS: This retrospective cohort study investigated eyes that received anti-VEGF therapy. All participants underwent comprehensive examinations and optical coherence tomography (OCT) volume scans at baseline (M0) and 1 month after the first treatment (M1). Two deep learning models were separately developed to automatically measure the CMFV and the CST. Correlations were analyzed between the CMFV and the logMAR BCVA at M0 and logMAR BCVA at M1. The area under the receiver operating characteristic curve (AUROC) of CMFV and CST for predicting eyes with BCVA [Formula: see text] 20/40 at M1 was analyzed. RESULTS: This study included 156 DME eyes from 89 patients. The median CMFV decreased from 0.272 (0.061–0.568) at M0 to 0.096 (0.018–0.307) mm(3) at M1. The CST decreased from 414 (293–575) to 322 (252–430) μm. The logMAR BCVA decreased from 0.523 (0.301–0.817) to 0.398 (0.222–0.699). Multivariate analysis demonstrated that the CMFV was the only significant factor for logMAR BCVA at both M0 (β = 0.199, p = 0.047) and M1 (β = 0.279, p = 0.004). The AUROC of CMFV for predicting eyes with BCVA [Formula: see text] 20/40 at M1 was 0.72, and the AUROC of CST was 0.69. CONCLUSIONS: Anti-VEGF therapy is an effective treatment for DME. Automated measured CMFV is a more accurate prognostic factor than CST for the initial anti-VEGF treatment outcome of DME. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s40123-023-00746-5.
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spelling pubmed-104418482023-08-22 Artificial Intelligence-Based Quantification of Central Macular Fluid Volume and VA Prediction for Diabetic Macular Edema Using OCT Images Ye, Xin Gao, Kun He, Shucheng Zhong, Xiaxing Shen, Yingjiao Wang, Yaqi Shao, Hang Shen, Lijun Ophthalmol Ther Original Research INTRODUCTION: We studied the correlation of central macular fluid volume (CMFV) and central subfield thickness (CST) with best-corrected visual acuity (BCVA) in treatment-naïve eyes with diabetic macular edema (DME) 1 month after anti-vascular endothelial growth factor (VEGF) therapy. METHODS: This retrospective cohort study investigated eyes that received anti-VEGF therapy. All participants underwent comprehensive examinations and optical coherence tomography (OCT) volume scans at baseline (M0) and 1 month after the first treatment (M1). Two deep learning models were separately developed to automatically measure the CMFV and the CST. Correlations were analyzed between the CMFV and the logMAR BCVA at M0 and logMAR BCVA at M1. The area under the receiver operating characteristic curve (AUROC) of CMFV and CST for predicting eyes with BCVA [Formula: see text] 20/40 at M1 was analyzed. RESULTS: This study included 156 DME eyes from 89 patients. The median CMFV decreased from 0.272 (0.061–0.568) at M0 to 0.096 (0.018–0.307) mm(3) at M1. The CST decreased from 414 (293–575) to 322 (252–430) μm. The logMAR BCVA decreased from 0.523 (0.301–0.817) to 0.398 (0.222–0.699). Multivariate analysis demonstrated that the CMFV was the only significant factor for logMAR BCVA at both M0 (β = 0.199, p = 0.047) and M1 (β = 0.279, p = 0.004). The AUROC of CMFV for predicting eyes with BCVA [Formula: see text] 20/40 at M1 was 0.72, and the AUROC of CST was 0.69. CONCLUSIONS: Anti-VEGF therapy is an effective treatment for DME. Automated measured CMFV is a more accurate prognostic factor than CST for the initial anti-VEGF treatment outcome of DME. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s40123-023-00746-5. Springer Healthcare 2023-06-15 2023-10 /pmc/articles/PMC10441848/ /pubmed/37318706 http://dx.doi.org/10.1007/s40123-023-00746-5 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by-nc/4.0/Open Access This article is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License, which permits any non-commercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc/4.0/ (https://creativecommons.org/licenses/by-nc/4.0/) .
spellingShingle Original Research
Ye, Xin
Gao, Kun
He, Shucheng
Zhong, Xiaxing
Shen, Yingjiao
Wang, Yaqi
Shao, Hang
Shen, Lijun
Artificial Intelligence-Based Quantification of Central Macular Fluid Volume and VA Prediction for Diabetic Macular Edema Using OCT Images
title Artificial Intelligence-Based Quantification of Central Macular Fluid Volume and VA Prediction for Diabetic Macular Edema Using OCT Images
title_full Artificial Intelligence-Based Quantification of Central Macular Fluid Volume and VA Prediction for Diabetic Macular Edema Using OCT Images
title_fullStr Artificial Intelligence-Based Quantification of Central Macular Fluid Volume and VA Prediction for Diabetic Macular Edema Using OCT Images
title_full_unstemmed Artificial Intelligence-Based Quantification of Central Macular Fluid Volume and VA Prediction for Diabetic Macular Edema Using OCT Images
title_short Artificial Intelligence-Based Quantification of Central Macular Fluid Volume and VA Prediction for Diabetic Macular Edema Using OCT Images
title_sort artificial intelligence-based quantification of central macular fluid volume and va prediction for diabetic macular edema using oct images
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10441848/
https://www.ncbi.nlm.nih.gov/pubmed/37318706
http://dx.doi.org/10.1007/s40123-023-00746-5
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