Uneven Index: A Digital Biomarker to Prompt Demodex Blepharitis Based on Deep Learning
Purpose: To evaluate ocular surface manifestations and morphological changes in meibomian glands (MGs) based on artificial intelligence (AI) analysis in patients with Demodex blepharitis.Methods: In this retrospective study, 115 subjects were enrolled, including 64 subjects with Demodex blepharitis...
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| Format: | Article |
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Frontiers Media S.A.
2022-07-01
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| Series: | Frontiers in Physiology |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fphys.2022.934821/full |
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| author | Xinyi Liu Xinyi Liu Yana Fu Yana Fu Dandan Wang Dandan Wang Shoujun Huang Chunlei He Xinxin Yu Zuhui Zhang Dexing Kong Qi Dai Qi Dai |
| author_facet | Xinyi Liu Xinyi Liu Yana Fu Yana Fu Dandan Wang Dandan Wang Shoujun Huang Chunlei He Xinxin Yu Zuhui Zhang Dexing Kong Qi Dai Qi Dai |
| author_sort | Xinyi Liu |
| collection | DOAJ |
| description | Purpose: To evaluate ocular surface manifestations and morphological changes in meibomian glands (MGs) based on artificial intelligence (AI) analysis in patients with Demodex blepharitis.Methods: In this retrospective study, 115 subjects were enrolled, including 64 subjects with Demodex blepharitis and 51 subjects without Demodex blepharitis as control group. Morphological indexes were evaluated for height, width, tortuosity, MG density, total variation, and the three types of corrected total variation as Uneven indexes.Results: There were no statistically significant differences in all MGs’ average tortuosity and width between the two groups. The average height of all MGs and MG density were significantly lower in the Demodex blepharitis group than control group. The total variation and two types of Uneven indexes were significantly higher in the Demodex blepharitis group than in the control group. Especially the Uneven Index of total variation/MG density had an AUC of 0.822. And the sensitivity and specificity were 59.4% and 92.2%, respectively, at a cut-off value of 3971.667. In addition, Demodex blepharitis was associated with significantly lower meibum quality and expressibility, severe atrophy of MGs, a higher ocular surface disease index (OSDI), and more instability of the tear film.Conclusion:Demodex mites are strongly associated with morphological changes in the MGs and may cause uneven gland atrophy. Therefore, the novel characteristic parameter, the Uneven index, may serve as a digital biomarker to evaluate uneven atrophy of MGs and prompt Demodex blepharitis. |
| first_indexed | 2024-12-11T14:58:43Z |
| format | Article |
| id | doaj.art-5e7726b8f6b34d568883a2cd36370392 |
| institution | Directory Open Access Journal |
| issn | 1664-042X |
| language | English |
| last_indexed | 2024-12-11T14:58:43Z |
| publishDate | 2022-07-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Physiology |
| spelling | doaj.art-5e7726b8f6b34d568883a2cd363703922022-12-22T01:01:13ZengFrontiers Media S.A.Frontiers in Physiology1664-042X2022-07-011310.3389/fphys.2022.934821934821Uneven Index: A Digital Biomarker to Prompt Demodex Blepharitis Based on Deep LearningXinyi Liu0Xinyi Liu1Yana Fu2Yana Fu3Dandan Wang4Dandan Wang5Shoujun Huang6Chunlei He7Xinxin Yu8Zuhui Zhang9Dexing Kong10Qi Dai11Qi Dai12School of Ophthalmology and Optometry, Eye Hospital Wenzhou Medical University, Wenzhou, ChinaDepartment of Ophthalmology, People’s Hospital of Yichun, Yichun, ChinaSchool of Ophthalmology and Optometry, Eye Hospital Wenzhou Medical University, Wenzhou, ChinaDepartment of Ophthalmology, Second Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, ChinaSchool of Ophthalmology and Optometry, Eye Hospital Wenzhou Medical University, Wenzhou, ChinaDepartment of Ophthalmology, The First Affiliated Hospital of Soochow University, Suzhou, ChinaCollege of Mathematical Medicine, Zhejiang Normal University, Jinhua, ChinaCollege of Mathematical Medicine, Zhejiang Normal University, Jinhua, ChinaSchool of Ophthalmology and Optometry, Eye Hospital Wenzhou Medical University, Wenzhou, ChinaSchool of Ophthalmology and Optometry, Eye Hospital Wenzhou Medical University, Wenzhou, ChinaCollege of Mathematical Medicine, Zhejiang Normal University, Jinhua, ChinaSchool of Ophthalmology and Optometry, Eye Hospital Wenzhou Medical University, Wenzhou, ChinaCollege of Mathematical Medicine, Zhejiang Normal University, Jinhua, ChinaPurpose: To evaluate ocular surface manifestations and morphological changes in meibomian glands (MGs) based on artificial intelligence (AI) analysis in patients with Demodex blepharitis.Methods: In this retrospective study, 115 subjects were enrolled, including 64 subjects with Demodex blepharitis and 51 subjects without Demodex blepharitis as control group. Morphological indexes were evaluated for height, width, tortuosity, MG density, total variation, and the three types of corrected total variation as Uneven indexes.Results: There were no statistically significant differences in all MGs’ average tortuosity and width between the two groups. The average height of all MGs and MG density were significantly lower in the Demodex blepharitis group than control group. The total variation and two types of Uneven indexes were significantly higher in the Demodex blepharitis group than in the control group. Especially the Uneven Index of total variation/MG density had an AUC of 0.822. And the sensitivity and specificity were 59.4% and 92.2%, respectively, at a cut-off value of 3971.667. In addition, Demodex blepharitis was associated with significantly lower meibum quality and expressibility, severe atrophy of MGs, a higher ocular surface disease index (OSDI), and more instability of the tear film.Conclusion:Demodex mites are strongly associated with morphological changes in the MGs and may cause uneven gland atrophy. Therefore, the novel characteristic parameter, the Uneven index, may serve as a digital biomarker to evaluate uneven atrophy of MGs and prompt Demodex blepharitis.https://www.frontiersin.org/articles/10.3389/fphys.2022.934821/fullartificial intelligenceDemodex blepharitisdigital biomarkertotal variationuneven atrophy |
| spellingShingle | Xinyi Liu Xinyi Liu Yana Fu Yana Fu Dandan Wang Dandan Wang Shoujun Huang Chunlei He Xinxin Yu Zuhui Zhang Dexing Kong Qi Dai Qi Dai Uneven Index: A Digital Biomarker to Prompt Demodex Blepharitis Based on Deep Learning Frontiers in Physiology artificial intelligence Demodex blepharitis digital biomarker total variation uneven atrophy |
| title | Uneven Index: A Digital Biomarker to Prompt Demodex Blepharitis Based on Deep Learning |
| title_full | Uneven Index: A Digital Biomarker to Prompt Demodex Blepharitis Based on Deep Learning |
| title_fullStr | Uneven Index: A Digital Biomarker to Prompt Demodex Blepharitis Based on Deep Learning |
| title_full_unstemmed | Uneven Index: A Digital Biomarker to Prompt Demodex Blepharitis Based on Deep Learning |
| title_short | Uneven Index: A Digital Biomarker to Prompt Demodex Blepharitis Based on Deep Learning |
| title_sort | uneven index a digital biomarker to prompt demodex blepharitis based on deep learning |
| topic | artificial intelligence Demodex blepharitis digital biomarker total variation uneven atrophy |
| url | https://www.frontiersin.org/articles/10.3389/fphys.2022.934821/full |
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