Tillmann, Anne; Turgut, Ferhat; Munk, Marion R. (2024). Optical coherence tomography angiography in neovascular age-related macular degeneration: comprehensive review of advancements and future perspective. (In Press). Eye Springer Nature 10.1038/s41433-024-03295-8
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Optical coherence tomography angiography (OCTA) holds promise in enhancing the care of various retinal vascular diseases, including neovascular age-related macular degeneration (nAMD). Given nAMD's vascular nature and the distinct vasculature of macular neovascularization (MNV), detailed analysis is expected to gain significance. Research in artificial intelligence (AI) indicates that en-face OCTA views may offer superior predictive capabilities than spectral domain optical coherence tomography (SD-OCT) images, highlighting the necessity to identify key vascular parameters. Analyzing vasculature could facilitate distinguishing MNV subtypes and refining diagnosis. Future studies correlating OCTA parameters with clinical data might prompt a revised classification system. However, the combined utilization of qualitative and quantitative OCTA biomarkers to enhance the accuracy of diagnosing disease activity remains underdeveloped. Discrepancies persist regarding the optimal biomarker for indicating an active lesion, warranting comprehensive prospective studies for validation. AI holds potential in extracting valuable insights from the vast datasets within OCTA, enabling researchers and clinicians to fully exploit its OCTA imaging capabilities. Nevertheless, challenges pertaining to data quantity and quality pose significant obstacles to AI advancement in this field. As OCTA gains traction in clinical practice and data volume increases, AI-driven analysis is expected to further augment diagnostic capabilities.
Item Type: |
Journal Article (Review Article) |
|---|---|
Division/Institute: |
04 Faculty of Medicine > Department of Head Organs and Neurology (DKNS) > Clinic of Ophthalmology |
Subjects: |
600 Technology > 610 Medicine & health |
ISSN: |
1476-5454 |
Publisher: |
Springer Nature |
Language: |
English |
Submitter: |
Pubmed Import |
Date Deposited: |
16 Aug 2024 10:02 |
Last Modified: |
16 Aug 2024 10:02 |
Publisher DOI: |
10.1038/s41433-024-03295-8 |
PubMed ID: |
39147864 |
BORIS DOI: |
10.48350/199757 |
URI: |
https://boris.unibe.ch/id/eprint/199757 |
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