Artificial intelligence for the detection of glaucoma with SD-OCT images: a systematic review and Meta-analysis
AIM: To quantify the performance of artificial intelligence (AI) in detecting glaucoma with spectral-domain optical coherence tomography (SD-OCT) images. METHODS: Electronic databases including PubMed, Embase, Scopus, ScienceDirect, ProQuest and Cochrane Library were searched before May 31, 2023 whi...
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| Format: | Article |
| Language: | English |
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Press of International Journal of Ophthalmology (IJO PRESS)
2024-03-01
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| Series: | International Journal of Ophthalmology |
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| Online Access: | http://ies.ijo.cn/en_publish/2024/3/20240302.pdf |
| _version_ | 1797293914643759104 |
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| author | Nan-Nan Shi Jing Li Guang-Hui Liu Ming-Fang Cao |
| author_facet | Nan-Nan Shi Jing Li Guang-Hui Liu Ming-Fang Cao |
| author_sort | Nan-Nan Shi |
| collection | DOAJ |
| description | AIM: To quantify the performance of artificial intelligence (AI) in detecting glaucoma with spectral-domain optical coherence tomography (SD-OCT) images. METHODS: Electronic databases including PubMed, Embase, Scopus, ScienceDirect, ProQuest and Cochrane Library were searched before May 31, 2023 which adopted AI for glaucoma detection with SD-OCT images. All pieces of the literature were screened and extracted by two investigators. Meta-analysis, Meta-regression, subgroup, and publication of bias were conducted by Stata16.0. The risk of bias assessment was performed in Revman5.4 using the QUADAS-2 tool. RESULTS: Twenty studies and 51 models were selected for systematic review and Meta-analysis. The pooled sensitivity and specificity were 0.91 (95%CI: 0.86–0.94, I2=94.67%), 0.90 (95%CI: 0.87–0.92, I2=89.24%). The pooled positive likelihood ratio (PLR) and negative likelihood ratio (NLR) were 8.79 (95%CI: 6.93–11.15, I2=89.31%) and 0.11 (95%CI: 0.07–0.16, I2=95.25%). The pooled diagnostic odds ratio (DOR) and area under curve (AUC) were 83.58 (95%CI: 47.15–148.15, I2=100%) and 0.95 (95%CI: 0.93–0.97). There was no threshold effect (Spearman correlation coefficient=0.22, P>0.05). CONCLUSION: There is a high accuracy for the detection of glaucoma with AI with SD-OCT images. The application of AI-based algorithms allows together with “doctor+artificial intelligence” to improve the diagnosis of glaucoma. |
| first_indexed | 2024-03-07T21:22:40Z |
| format | Article |
| id | doaj.art-21d3086ab692433191f581eb05acb65a |
| institution | Directory Open Access Journal |
| issn | 2222-3959 2227-4898 |
| language | English |
| last_indexed | 2024-03-07T21:22:40Z |
| publishDate | 2024-03-01 |
| publisher | Press of International Journal of Ophthalmology (IJO PRESS) |
| record_format | Article |
| series | International Journal of Ophthalmology |
| spelling | doaj.art-21d3086ab692433191f581eb05acb65a2024-02-27T08:51:41ZengPress of International Journal of Ophthalmology (IJO PRESS)International Journal of Ophthalmology2222-39592227-48982024-03-0117340841910.18240/ijo.2024.03.0220240302Artificial intelligence for the detection of glaucoma with SD-OCT images: a systematic review and Meta-analysisNan-Nan Shi0Jing Li1Guang-Hui Liu2Ming-Fang Cao3Ming-Fang Cao and Guang-Hui Liu. Department of Ophthalmology, Affiliated People's Hospital (Fujian Provincial People's Hospital), Fujian University of Traditional Chinese Medicine, 602 817 Middle Road, Taijiang District, Fuzhou 350004, Fujian Province, China. farrahcao@126.com; latiny@gmail.comDepartment of Ophthalmology, Affiliated People's Hospital (Fujian Provincial People's Hospital), Fujian University of Traditional Chinese Medicine, Fuzhou 350004, Fujian Province, China; Eye Institute of Integrated Chinese and Western Medicine, Fujian University of Traditional Chinese Medicine, Fuzhou 350004, Fujian Province, ChinaDepartment of Ophthalmology, Affiliated People's Hospital (Fujian Provincial People's Hospital), Fujian University of Traditional Chinese Medicine, Fuzhou 350004, Fujian Province, China; Eye Institute of Integrated Chinese and Western Medicine, Fujian University of Traditional Chinese Medicine, Fuzhou 350004, Fujian Province, ChinaDepartment of Ophthalmology, Affiliated People's Hospital (Fujian Provincial People's Hospital), Fujian University of Traditional Chinese Medicine, Fuzhou 350004, Fujian Province, China; Eye Institute of Integrated Chinese and Western Medicine, Fujian University of Traditional Chinese Medicine, Fuzhou 350004, Fujian Province, ChinaAIM: To quantify the performance of artificial intelligence (AI) in detecting glaucoma with spectral-domain optical coherence tomography (SD-OCT) images. METHODS: Electronic databases including PubMed, Embase, Scopus, ScienceDirect, ProQuest and Cochrane Library were searched before May 31, 2023 which adopted AI for glaucoma detection with SD-OCT images. All pieces of the literature were screened and extracted by two investigators. Meta-analysis, Meta-regression, subgroup, and publication of bias were conducted by Stata16.0. The risk of bias assessment was performed in Revman5.4 using the QUADAS-2 tool. RESULTS: Twenty studies and 51 models were selected for systematic review and Meta-analysis. The pooled sensitivity and specificity were 0.91 (95%CI: 0.86–0.94, I2=94.67%), 0.90 (95%CI: 0.87–0.92, I2=89.24%). The pooled positive likelihood ratio (PLR) and negative likelihood ratio (NLR) were 8.79 (95%CI: 6.93–11.15, I2=89.31%) and 0.11 (95%CI: 0.07–0.16, I2=95.25%). The pooled diagnostic odds ratio (DOR) and area under curve (AUC) were 83.58 (95%CI: 47.15–148.15, I2=100%) and 0.95 (95%CI: 0.93–0.97). There was no threshold effect (Spearman correlation coefficient=0.22, P>0.05). CONCLUSION: There is a high accuracy for the detection of glaucoma with AI with SD-OCT images. The application of AI-based algorithms allows together with “doctor+artificial intelligence” to improve the diagnosis of glaucoma.http://ies.ijo.cn/en_publish/2024/3/20240302.pdfartificial intelligencespectral-domain optical coherence tomographyglaucomameta-analysis |
| spellingShingle | Nan-Nan Shi Jing Li Guang-Hui Liu Ming-Fang Cao Artificial intelligence for the detection of glaucoma with SD-OCT images: a systematic review and Meta-analysis International Journal of Ophthalmology artificial intelligence spectral-domain optical coherence tomography glaucoma meta-analysis |
| title | Artificial intelligence for the detection of glaucoma with SD-OCT images: a systematic review and Meta-analysis |
| title_full | Artificial intelligence for the detection of glaucoma with SD-OCT images: a systematic review and Meta-analysis |
| title_fullStr | Artificial intelligence for the detection of glaucoma with SD-OCT images: a systematic review and Meta-analysis |
| title_full_unstemmed | Artificial intelligence for the detection of glaucoma with SD-OCT images: a systematic review and Meta-analysis |
| title_short | Artificial intelligence for the detection of glaucoma with SD-OCT images: a systematic review and Meta-analysis |
| title_sort | artificial intelligence for the detection of glaucoma with sd oct images a systematic review and meta analysis |
| topic | artificial intelligence spectral-domain optical coherence tomography glaucoma meta-analysis |
| url | http://ies.ijo.cn/en_publish/2024/3/20240302.pdf |
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