Evidence map›Paper›PMID 40606272›Full record

ArticleFrontiers in cellular neuroscience2025

Evaluation of retinal structure changes with AI-based OCT image segmentation for sodium iodate induced retinal degeneration.

Yong Zeng, Jiaming Zhou, Yichao Li, Bruno Alvisio, Jacob Czech, David Bissig, Haohua Qian

Abstract read
In one paragraph

Article in Frontiers in cellular neuroscience, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Yong Zeng *Visual Function Core, National Eye Institute, National Institutes of Health, Bethesda, MD, United States.
Jiaming Zhou *Visual Function Core, National Eye Institute, National Institutes of Health, Bethesda, MD, United States.
Yichao LiVisual Function Core, National Eye Institute, National Institutes of Health, Bethesda, MD, United States.
Bruno AlvisioOSIO Bioinformatics Core, National Eye Institute, National Institutes of Health, Bethesda, MD, United States.
Jacob CzechOSIO Bioinformatics Core, National Eye Institute, National Institutes of Health, Bethesda, MD, United States.
David BissigDepartment of Neurology, University of California, Davis, Sacramento, CA, United States.
Haohua QianVisual Function Core, National Eye Institute, National Institutes of Health, Bethesda, MD, United States.

Funding

Illuminating Glial Dysfunction in Alzheimer’s Disease with Optical Coherence TomographyK08AG080178 · NIA · UNIVERSITY OF CALIFORNIA AT DAVIS · PI David Philip Bissig · 2023 to 2026
$656k
NIA NIH HHS K08 AG080178
6 · The paper itself

Abstract

Segmentations of retinal optical coherence tomography (OCT) images provide valuable information about each specific retinal layer. However, processing images from degenerative retina remains challenging. This study developed artificial intelligence (AI)-based segmentation to analyze structure changes in sodium iodate (SI)-treated mice. The software is capable of segmenting seven retinal layers and one choroid layer. Analyzing OCT images captured at days post SI-injection (PI) revealed early changes in the retinal pigment epithelium (RPE) layer, with increase in thickness and reduction in reflectance calculated by estimated Attenuation Coefficients (eAC). On the other hand, eAC for outer nuclear layer (ONL) exhibited early and sustained increase after SI treatment. SI induced exponential reduction in ONL thickness with a half-reduction time of about 3 days, indicating progressive photoreceptor degeneration. The extent of degeneration was correlated with ONL eAC level at PI1. Inner retinal layers showed bi-phasic reactions, with initial increases in layer thickness that peaked at around PI3, followed by gradual reduction to lower than baseline levels. In addition, SI also induced transient increases in vitreous particles concentrated around the optic nerve head. Furthermore, there was a gradual reduction of choroid thickness after SI treatment. These results indicate the AI-segmentation tool's usefulness for providing a sensitive and accurate assessment of structure changes in diseased retina and revealed more detailed characterization of SI-induced degeneration in all retinal layers with distinct time courses. Our results also support ONL reflectance changes as an early biomarker for retinal degeneration.

Indexed as

artificial intelligencebiomarkerchoroidmouseoptical coherence tomographyretinasegmentationsodium iodate

Identifiers

PMID40606272
PMCPMC12213626

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.