Document Type

Article

Publication Date

5-2022

Publisher

Association for Research in Vision and Ophthalmology

Source Publication

Translation Vision Science & Technology

Source ISSN

2164-2591

Original Item ID

DOI: 10.1167/tvst.11.5.19

Abstract

Purpose: To compare cone mosaic metrics derived from adaptive optics scanning light ophthalmoscopy (AOSLO) images with those derived from Heidelberg Engineering SPECTRALIS High Magnification Module (HMM) images.

Methods: Participants with contiguous cone mosaics had HMM imaging performed at locations superior and temporal to the fovea. These images were registered and averaged offline and then aligned to split-detection AOSLO images; 200 × 200-µm regions of interest were extracted from both modalities. Cones were semi-automatically identified by two graders to provide estimates of cone density and spacing.

Results: Thirty participants with contiguous cone mosaics were imaged (10 males, 20 females; age range, 11–67 years). Image quality varied, and 80% of our participants had analyzable HMM images. The intergrader intraclass correlation coefficients for cone metrics were good for both modalities (0.688–0.757 for HMM; 0.805–0.836 for AOSLO). Cone density estimates from HMM images were lower by 2661 cones/mm2 (24.1%) on average compared to AOSLO-derived estimates. Accordingly, HMM estimates of cone spacing were increased on average compared to AOSLO.

Conclusions: The cone mosaic can be visualized in vivo using the SPECTRALIS HMM, although image quality is variable and imaging is not successful in every individual. Metrics extracted from HMM images can differ from those from AOSLO, although excellent agreement is possible in individuals with excellent optical quality and precise co-registration between modalities.

Translational Relevance: Emerging non-adaptive optics-based photoreceptor imaging is more clinically accessible than adaptive optics techniques and has potential to expand high-resolution imaging in a clinical environment.

Comments

Published version. Translational Vision Science & Technology, Vol. 11, No. 5 (May 2022). DOI. © The Authors, published by the Association for Research in Vision and Ophthalmology. Used with permission.

Creative Commons License

Creative Commons Attribution 4.0 International License
This work is licensed under a Creative Commons Attribution 4.0 International License.

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