Evidence map›Paper›PMID 38472220›Full record

ArticleScientific reports2024

Towards standardising retinal OCT angiography image analysis with open-source toolbox OCTAVA.

Gavrielle R Untracht, Madeleine S Durkee, Mei Zhao, Andrew Kwok-Cheung Lam, Bartosz L Sikorski, Marinko V Sarunic, Peter E Andersen, David D Sampson, Fred K Chen, Danuta M Sampson

Abstract read
In one paragraph

Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
30citing papers in PubMed, 1 pooled it
–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

30 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. AI-driven multimodal retinal imaging for early detection and risk stratification of vascular and neurodegenerative diseases.Graefe's archive for clinical and experimental ophthalmology = Albrecht von Graefes Archiv fur klinische und experimentelle Ophthalmologie · 2026
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  16. OCTA-ReVABiomedical optics express · 2025
    Article
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  19. Review
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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

10 authors.

Gavrielle R UntrachtDepartment of Health Technology, Technical University of Denmark, 2800, Kongens Lyngby, Denmark.
Madeleine S DurkeeDepartment of Radiology, University of Chicago, Chicago, IL, 60637, USA.
Mei ZhaoCentre for Myopia Research, School of Optometry, Faculty of Health and Social Science, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong, China.
Andrew Kwok-Cheung LamCentre for Myopia Research, School of Optometry, Faculty of Health and Social Science, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong, China.
Bartosz L SikorskiDepartment of Ophthalmology, Nicolaus Copernicus University, 85-090, Bydgoszcz, Poland.
Marinko V SarunicDepartment of Medical Physics and Biomedical Engineering, University College London, London, WC1E6BT, UK.
Peter E AndersenDepartment of Health Technology, Technical University of Denmark, 2800, Kongens Lyngby, Denmark.
David D SampsonSchool of Computer Science and Electronic Engineering, The University of Surrey, Guildford, GU27XH, UK.
Fred K ChenCentre for Ophthalmology and Visual Science (Incorporating Lions Eye Institute), The University of Western Australia, Perth, WA, 6009, Australia.
Danuta M SampsonSchool of Biosciences, The University of Surrey, Guildford, GU27XH, UK. Danuta.sampson@uwa.edu.au.

Funding

Horizon 2020 Framework Programme 871212
6 · The paper itself

Abstract

Quantitative assessment of retinal microvasculature in optical coherence tomography angiography (OCTA) images is important for studying, diagnosing, monitoring, and guiding the treatment of ocular and systemic diseases. However, the OCTA user community lacks universal and transparent image analysis tools that can be applied to images from a range of OCTA instruments and provide reliable and consistent microvascular metrics from diverse datasets. We present a retinal extension to the OCTA Vascular Analyser (OCTAVA) that addresses the challenges of providing robust, easy-to-use, and transparent analysis of retinal OCTA images. OCTAVA is a user-friendly, open-source toolbox that can analyse retinal OCTA images from various instruments. The toolbox delivers seven microvascular metrics for the whole image or subregions and six metrics characterising the foveal avascular zone. We validate OCTAVA using images collected by four commercial OCTA instruments demonstrating robust performance across datasets from different instruments acquired at different sites from different study cohorts. We show that OCTAVA delivers values for retinal microvascular metrics comparable to the literature and reduces their variation between studies compared to their commercial equivalents. By making OCTAVA publicly available, we aim to expand standardised research and thereby improve the reproducibility of quantitative analysis of retinal microvascular imaging. Such improvements will help to better identify more reliable and sensitive biomarkers of ocular and systemic diseases.

Indexed as

Macula LuteaRetinal VesselsFluorescein AngiographyMicrovesselsReproducibility of ResultsTomography, Optical Coherence

Identifiers

PMID38472220
PMCPMC10933365

What OpenQuestion holds

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Registered trials

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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.