Clinical validation for automated geographic atrophy monitoring on OCT under complement inhibitory treatment
Abstract Geographic atrophy (GA) represents a late stage of age-related macular degeneration, which leads to irreversible vision loss. With the first successful therapeutic approach, namely complement inhibition, huge numbers of patients will have to be monitored regularly. Given these perspectives,...
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Nature Portfolio
2023-04-01
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| Series: | Scientific Reports |
| Online Access: | https://doi.org/10.1038/s41598-023-34139-2 |
| _version_ | 1797836466670272512 |
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| author | Julia Mai Dmitrii Lachinov Sophie Riedl Gregor S. Reiter Wolf-Dieter Vogl Hrvoje Bogunovic Ursula Schmidt-Erfurth |
| author_facet | Julia Mai Dmitrii Lachinov Sophie Riedl Gregor S. Reiter Wolf-Dieter Vogl Hrvoje Bogunovic Ursula Schmidt-Erfurth |
| author_sort | Julia Mai |
| collection | DOAJ |
| description | Abstract Geographic atrophy (GA) represents a late stage of age-related macular degeneration, which leads to irreversible vision loss. With the first successful therapeutic approach, namely complement inhibition, huge numbers of patients will have to be monitored regularly. Given these perspectives, a strong need for automated GA segmentation has evolved. The main purpose of this study was the clinical validation of an artificial intelligence (AI)-based algorithm to segment a topographic 2D GA area on a 3D optical coherence tomography (OCT) volume, and to evaluate its potential for AI-based monitoring of GA progression under complement-targeted treatment. 100 GA patients from routine clinical care at the Medical University of Vienna for internal validation and 113 patients from the FILLY phase 2 clinical trial for external validation were included. Mean Dice Similarity Coefficient (DSC) was 0.86 ± 0.12 and 0.91 ± 0.05 for total GA area on the internal and external validation, respectively. Mean DSC for the GA growth area at month 12 on the external test set was 0.46 ± 0.16. Importantly, the automated segmentation by the algorithm corresponded to the outcome of the original FILLY trial measured manually on fundus autofluorescence. The proposed AI approach can reliably segment GA area on OCT with high accuracy. The availability of such tools represents an important step towards AI-based monitoring of GA progression under treatment on OCT for clinical management as well as regulatory trials. |
| first_indexed | 2024-04-09T15:10:24Z |
| format | Article |
| id | doaj.art-279df9754cdc4957b46f1794ec381352 |
| institution | Directory Open Access Journal |
| issn | 2045-2322 |
| language | English |
| last_indexed | 2024-04-09T15:10:24Z |
| publishDate | 2023-04-01 |
| publisher | Nature Portfolio |
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| series | Scientific Reports |
| spelling | doaj.art-279df9754cdc4957b46f1794ec3813522023-04-30T11:13:50ZengNature PortfolioScientific Reports2045-23222023-04-0113111110.1038/s41598-023-34139-2Clinical validation for automated geographic atrophy monitoring on OCT under complement inhibitory treatmentJulia Mai0Dmitrii Lachinov1Sophie Riedl2Gregor S. Reiter3Wolf-Dieter Vogl4Hrvoje Bogunovic5Ursula Schmidt-Erfurth6Laboratory for Ophthalmic Image Analysis (OPTIMA), Department of Ophthalmology and Optometry, Medical University of ViennaLaboratory for Ophthalmic Image Analysis (OPTIMA), Department of Ophthalmology and Optometry, Medical University of ViennaLaboratory for Ophthalmic Image Analysis (OPTIMA), Department of Ophthalmology and Optometry, Medical University of ViennaLaboratory for Ophthalmic Image Analysis (OPTIMA), Department of Ophthalmology and Optometry, Medical University of ViennaLaboratory for Ophthalmic Image Analysis (OPTIMA), Department of Ophthalmology and Optometry, Medical University of ViennaLaboratory for Ophthalmic Image Analysis (OPTIMA), Department of Ophthalmology and Optometry, Medical University of ViennaLaboratory for Ophthalmic Image Analysis (OPTIMA), Department of Ophthalmology and Optometry, Medical University of ViennaAbstract Geographic atrophy (GA) represents a late stage of age-related macular degeneration, which leads to irreversible vision loss. With the first successful therapeutic approach, namely complement inhibition, huge numbers of patients will have to be monitored regularly. Given these perspectives, a strong need for automated GA segmentation has evolved. The main purpose of this study was the clinical validation of an artificial intelligence (AI)-based algorithm to segment a topographic 2D GA area on a 3D optical coherence tomography (OCT) volume, and to evaluate its potential for AI-based monitoring of GA progression under complement-targeted treatment. 100 GA patients from routine clinical care at the Medical University of Vienna for internal validation and 113 patients from the FILLY phase 2 clinical trial for external validation were included. Mean Dice Similarity Coefficient (DSC) was 0.86 ± 0.12 and 0.91 ± 0.05 for total GA area on the internal and external validation, respectively. Mean DSC for the GA growth area at month 12 on the external test set was 0.46 ± 0.16. Importantly, the automated segmentation by the algorithm corresponded to the outcome of the original FILLY trial measured manually on fundus autofluorescence. The proposed AI approach can reliably segment GA area on OCT with high accuracy. The availability of such tools represents an important step towards AI-based monitoring of GA progression under treatment on OCT for clinical management as well as regulatory trials.https://doi.org/10.1038/s41598-023-34139-2 |
| spellingShingle | Julia Mai Dmitrii Lachinov Sophie Riedl Gregor S. Reiter Wolf-Dieter Vogl Hrvoje Bogunovic Ursula Schmidt-Erfurth Clinical validation for automated geographic atrophy monitoring on OCT under complement inhibitory treatment Scientific Reports |
| title | Clinical validation for automated geographic atrophy monitoring on OCT under complement inhibitory treatment |
| title_full | Clinical validation for automated geographic atrophy monitoring on OCT under complement inhibitory treatment |
| title_fullStr | Clinical validation for automated geographic atrophy monitoring on OCT under complement inhibitory treatment |
| title_full_unstemmed | Clinical validation for automated geographic atrophy monitoring on OCT under complement inhibitory treatment |
| title_short | Clinical validation for automated geographic atrophy monitoring on OCT under complement inhibitory treatment |
| title_sort | clinical validation for automated geographic atrophy monitoring on oct under complement inhibitory treatment |
| url | https://doi.org/10.1038/s41598-023-34139-2 |
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