Evidence map›Paper›PMID 39901220›Full record

ArticleEuropean journal of medical research2025

Comparative analysis of ocular biometrics using spectral domain optical coherence tomography with Purkinje image and optic nerve head alignments in mice.

Ying Hon Sze, Bing Zuo, Da Qian Lu, King Kit Li, Dennis Yan Yin Tse, Qian Zhao, Thomas Chuen Lam

Abstract readComparative Study
In one paragraph

Article in European journal of medical research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

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

2 citing papers in PubMed.

  1. Spontaneous whole retinal degeneration in aged Beclin1 heterozygous mice.Journal of neural transmission (Vienna, Austria : 1996) · 2026
    Article
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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.

Ying Hon SzeCentre for Myopia Research, School of Optometry, The Hong Kong Polytechnic University, Hong Kong, China.
Bing ZuoCentre for Myopia Research, School of Optometry, The Hong Kong Polytechnic University, Hong Kong, China.
Da Qian LuCentre for Myopia Research, School of Optometry, The Hong Kong Polytechnic University, Hong Kong, China.
King Kit LiCentre for Myopia Research, School of Optometry, The Hong Kong Polytechnic University, Hong Kong, China.
Dennis Yan Yin TseCentre for Myopia Research, School of Optometry, The Hong Kong Polytechnic University, Hong Kong, China.
Qian ZhaoState Key Laboratory of Chemical Biology and Drug Discovery, Department of Applied Biology and Chemical Technology, The Hong Kong Polytechnic University, Hong Kong, China.
Thomas Chuen LamCentre for Myopia Research, School of Optometry, The Hong Kong Polytechnic University, Hong Kong, China. thomas.c.lam@polyu.edu.hk.

Funding

General Research Fund (GRF) 15104819General Research Fund (GRF) 151060/18MResearch Centre for SHARP Vision P0039545Research Centre for SHARP Vision P0043871Research Impact Fund R5032-18Shenzhen Science and Technology Innovation Commission JCY20180507183409601The Hong Kong Polytechnic University and the RGC-CRF equipment grant C5033-19E
6 · The paper itself

Abstract

backgroundMice are an emerging model for experimental myopia. Due to their small eye size, non-invasive optical coherence tomography is essential for evaluating ocular biometrics. There is currently no universally accepted protocol for those measurements. This study aims to compare ocular biometric measurements using two methods: Purkinje image-based alignment and optic nerve head alignment, utilizing spectral domain optical coherence tomography. Gaining an understanding of the implications of these methods in determining axial elongation in the normal growing eyes of wild-type C57BL/6J mice would offer valuable insight into their relevance for the experimental myopia model.

methodsOcular dimensions and refractive development were measured on postnatal days P21 (n = 10), P28 (n = 15), and P35 (n = 8). The Purkinje image-based alignment (P1) was determined using a photorefractor and aligned perpendicular to the corneal apex using SD-OCT. In comparison, due to the absence of a fovea in the mouse retina, the optic nerve head (ONH) alignment was used. Variance analysis, regression analysis, and Bland-Altman analysis were performed to compare the differences between alignment methods as well as the replication by another operator.

resultsMice developed hyperopic ametropia under normal visual conditions. The photorefractor measured a technical variation of 3.9 D (95% CI, n = 170, triplicates). Bland-Altman analysis revealed a shorter (mean ± SD) axial length (- 26.4 ± 18.1 μm) and vitreous chamber depth (- 39.9 ± 25.4 μm) in the Purkinje image-based alignment. There was a significant difference in the relative growth trend in VCD (linear regression, p = 0.02), which was relatively stable and showed shortening when measured with ONH alignment from postnatal age 21 to 35 days.

conclusionsSD-OCT allowed precise in-vivo measurement and segmentation of ocular dimensions, regardless of the methods adopted. P1 alignment consistently resulted in significantly shorter VCD and AL compared to ONH alignment at most time points. When considering temporal changes from P21 to P35, both methods showed similar results, with significant elongation of ACD, LT, and AL as expected. However, our findings revealed a significant shortening of VCD over time with the adoption of ONH alignment, while the change in P1 alignment was relatively stable. Therefore, AL provides a better measure for evaluating ocular growth in mice using optical coherence tomography than VCD for myopia research.

Indexed as

BiometryEyeMyopiaOptic DiskTomography, Optical CoherenceAnimalsDisease Models, AnimalMiceMice, Inbred C57BL

Identifiers

PMID39901220
PMCPMC11789383

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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.