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von der Emde, L.* ; Rennen, G.C.* ; Vaisband, M.* ; Hasenauer, J. ; Liegl, R.* ; Fleckenstein, M.* ; Pfau, M.* ; Holz, F.G.* ; Ach, T.*

Impact of lens autofluorescence and opacification on retinal imaging.

BMJ Open Ophthalmol. 9:e001628 (2024)
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BACKGROUND: Retinal imaging, including fundus autofluorescence (FAF), strongly depends on the clearness of the optical media. Lens status is crucial since the ageing lens has both light-blocking and autofluorescence (AF) properties that distort image analysis. Here, we report both lens opacification and AF metrics and the effect on automated image quality assessment. METHODS: 227 subjects (range: 19-89 years old) received quantitative AF of the lens (LQAF), Scheimpflug, anterior chamber optical coherence tomography as well as blue/green FAF (BAF/GAF), and infrared (IR) imaging. LQAF values, the Pentacam Nucleus Staging score and the relative lens reflectivity were extracted to estimate lens opacification. Mean opinion scores of FAF and IR image quality were compiled by medical readers. A regression model for predicting image quality was developed using a convolutional neural network (CNN). Correlation analysis was conducted to assess the association of lens scores, with retinal image quality derived from human or CNN annotations. RESULTS: Retinal image quality was generally high across all imaging modalities (IR (8.25±1.99) >GAF >BAF (6.6±3.13)). CNN image quality prediction was excellent (average mean absolute error (MAE) 0.9). Predictions were comparable to human grading. Overall, LQAF showed the highest correlation with image quality grading criteria for all imaging modalities (eg, Pearson correlation±CI -0.35 (-0.50 to 0.18) for BAF/LQAF). BAF image quality was most vulnerable to an increase in lenticular metrics, while IR (-0.19 (-0.38 to 0.01)) demonstrated the highest resilience. CONCLUSION: The use of CNN-based retinal image quality assessment achieved excellent results. The study highlights the vulnerability of BAF to lenticular remodelling. These results can aid in the development of cut-off values for clinical studies, ensuring reliable data collection for the monitoring of retinal diseases.
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Publication type Article: Journal article
Document type Scientific Article
Corresponding Author
Keywords Imaging ; Lens And Zonules ; Macula ; Retina; Quantitative Fundus Autofluorescence; Crystalline Lens; Oct; Transmission; System
ISSN (print) / ISBN 2397-3269
e-ISSN 2397-3269
Journal BMJ Open Ophthalmology
Quellenangaben Volume: 9, Issue: 1, Pages: , Article Number: e001628 Supplement: ,
Publisher BMJ Publishing Group
Publishing Place British Med Assoc House, Tavistock Square, London Wc1h 9jr, England
Non-patent literature Publications
Reviewing status Peer reviewed
Institute(s) Institute of Computational Biology (ICB)
Grants
NIH/NEI
Research to Prevent Blindness, New York, NY
BONFOR/SciMed Grant
Jackstaedt Foundation