Evidence map›Paper›PMID 30335815›Full record

ArticlePloS one2018

Comparison of methods to quantify macular and peripapillary vessel density in optical coherence tomography angiography.

Alessandro Rabiolo, Francesco Gelormini, Riccardo Sacconi, Maria Vittoria Cicinelli, Giacinto Triolo, Paolo Bettin, Kouros Nouri-Mahdavi, Francesco Bandello, Giuseppe Querques

Abstract readValidation Study
In one paragraph

Article in PloS one, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 82 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
82citing papers in PubMed, 3 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

82 citing papers in PubMed, 3 syntheses or guidelines pooled it.

  1. Pooled it
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  8. Inflammatory hematological ratios and subclinical microvascular changes of fundus in Behçet disease.Graefe's archive for clinical and experimental ophthalmology = Albrecht von Graefes Archiv fur klinische und experimentelle Ophthalmologie · 2025
    Article
  9. Advances in OCT Angiography.Translational vision science & technology · 2025
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22 more citing papers are in PubMed but not listed here.

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

9 authors.

Alessandro RabioloDepartment of Ophthalmology, University Vita-Salute, IRCCS San Raffaele, Milan, Italy.
Francesco GelorminiDepartment of Ophthalmology, University Vita-Salute, IRCCS San Raffaele, Milan, Italy.
Riccardo SacconiDepartment of Ophthalmology, University Vita-Salute, IRCCS San Raffaele, Milan, Italy.
Maria Vittoria CicinelliDepartment of Ophthalmology, University Vita-Salute, IRCCS San Raffaele, Milan, Italy.
Giacinto TrioloDepartment of Ophthalmology, University Vita-Salute, IRCCS San Raffaele, Milan, Italy.
Paolo BettinDepartment of Ophthalmology, University Vita-Salute, IRCCS San Raffaele, Milan, Italy.
Kouros Nouri-MahdaviStein Eye Institute, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California, United States of America.
Francesco BandelloDepartment of Ophthalmology, University Vita-Salute, IRCCS San Raffaele, Milan, Italy.
Giuseppe QuerquesDepartment of Ophthalmology, University Vita-Salute, IRCCS San Raffaele, Milan, Italy.ORCID 0000-0002-3292-9581

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeTo compare macular and peripapillary vessel density values calculated on optical coherence tomography angiography (OCT-A) images with different algorithms, elaborate conversion formula, and compare the ability to discriminate healthy from affected eyes.

methodsCross-sectional study of healthy subjects, patients with diabetic retinopathy, and glaucoma patients (44 eyes in each group). Vessel density in the macular superficial capillary plexus (SCP), deep capillary plexus (DCP), and the peripapillary radial capillary plexus (RCP) were calculated with seven previously published algorithms. Systemic differences, diagnostic properties, reliability, and agreement of the methods were investigated.

resultsHealthy eyes exhibited higher vessel density values in all plexuses compared to diseased eyes regardless of the algorithm used (p<0.01). The estimated vessel densities were significantly different at all the plexuses (p<0.0001) as a function of method used. Inter-method reliability and agreement was mostly poor to moderate. A conversion formula was available for every method, except for the conversion between multilevel and fixed at the DCP. Substantial systemic, non-constant biases were evident between many algorithms. No algorithm outperformed the others for discrimination of patients from healthy subjects in all the retinal plexuses, but the best performing algorithm varied with the selected plexus.

conclusionsAbsolute vessel density values calculated with different algorithms are not directly interchangeable. Differences between healthy and affected eyes could be appreciated with all methods with different discriminatory abilities as a function of the plexus analyzed. Longitudinal monitoring of vessel density should be performed with the same algorithm. Studies adopting vessel density as an outcome measure should not rely on external normative databases.

Indexed as

AdultAgedAlgorithmsCapillariesComputed Tomography AngiographyCross-Sectional StudiesDiabetic RetinopathyFemaleGlaucomaHealthy VolunteersHumansImage Processing, Computer-AssistedMacula LuteaMaleMiddle AgedReproducibility of Results

Identifiers

PMID30335815
PMCPMC6193681

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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.