Artificial Intelligence-Based Quantification of Central Macular Fluid Volume and VA Prediction for Diabetic Macular Edema Using OCT Images
Abstract 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. Method...
| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | English |
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Adis, Springer Healthcare
2023-06-01
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| Series: | Ophthalmology and Therapy |
| Subjects: | |
| Online Access: | https://doi.org/10.1007/s40123-023-00746-5 |
| _version_ | 1797736436986806272 |
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| author | Xin Ye Kun Gao Shucheng He Xiaxing Zhong Yingjiao Shen Yaqi Wang Hang Shao Lijun Shen |
| author_facet | Xin Ye Kun Gao Shucheng He Xiaxing Zhong Yingjiao Shen Yaqi Wang Hang Shao Lijun Shen |
| author_sort | Xin Ye |
| collection | DOAJ |
| description | Abstract 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 $$\ge$$ ≥ 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) mm3 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 $$\ge$$ ≥ 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. |
| first_indexed | 2024-03-12T13:13:53Z |
| format | Article |
| id | doaj.art-d1fb934a13a94cc38b70445850afe344 |
| institution | Directory Open Access Journal |
| issn | 2193-8245 2193-6528 |
| language | English |
| last_indexed | 2024-03-12T13:13:53Z |
| publishDate | 2023-06-01 |
| publisher | Adis, Springer Healthcare |
| record_format | Article |
| series | Ophthalmology and Therapy |
| spelling | doaj.art-d1fb934a13a94cc38b70445850afe3442023-08-27T11:11:38ZengAdis, Springer HealthcareOphthalmology and Therapy2193-82452193-65282023-06-011252441245210.1007/s40123-023-00746-5Artificial Intelligence-Based Quantification of Central Macular Fluid Volume and VA Prediction for Diabetic Macular Edema Using OCT ImagesXin Ye0Kun Gao1Shucheng He2Xiaxing Zhong3Yingjiao Shen4Yaqi Wang5Hang Shao6Lijun Shen7Department of Ophthalmology, Center for Rehabilitation Medicine, Zhejiang Provincial People’s Hospital (Affiliated People’s Hospital, Hangzhou Medical College)Jiaxing Key Laboratory of Visual Big Data and Artificial Intelligence, Yangtze Delta Region Institute of Tsinghua UniversityWenzhou Medical UniversityWenzhou Medical UniversityWenzhou Medical UniversityCollege of Media Engineering, Communication University of ZhejiangJiaxing Key Laboratory of Visual Big Data and Artificial Intelligence, Yangtze Delta Region Institute of Tsinghua UniversityDepartment of Ophthalmology, Center for Rehabilitation Medicine, Zhejiang Provincial People’s Hospital (Affiliated People’s Hospital, Hangzhou Medical College)Abstract 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 $$\ge$$ ≥ 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) mm3 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 $$\ge$$ ≥ 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.https://doi.org/10.1007/s40123-023-00746-5Anti-vascular endothelial growth factorArtificial intelligenceCentral macular fluid volumeCentral subfield thicknessDiabetic macular edemaOptical coherence tomography |
| spellingShingle | Xin Ye Kun Gao Shucheng He Xiaxing Zhong Yingjiao Shen Yaqi Wang Hang Shao Lijun Shen Artificial Intelligence-Based Quantification of Central Macular Fluid Volume and VA Prediction for Diabetic Macular Edema Using OCT Images Ophthalmology and Therapy Anti-vascular endothelial growth factor Artificial intelligence Central macular fluid volume Central subfield thickness Diabetic macular edema Optical coherence tomography |
| 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 | Anti-vascular endothelial growth factor Artificial intelligence Central macular fluid volume Central subfield thickness Diabetic macular edema Optical coherence tomography |
| url | https://doi.org/10.1007/s40123-023-00746-5 |
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