Evidence map›Paper›PMID 32855849›Full record

ArticleTranslational vision science & technology2020

Quantitative Fundus Autofluorescence: Advanced Analysis Tools.

Nikolai Kleefeldt, Katharina Bermond, Ioana-Sandra Tarau, Jost Hillenkamp, Andreas Berlin, Kenneth R Sloan, Thomas Ach

Open access · goldAbstract read
In one paragraph

Article in Translational vision science & technology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed
2.2field-weighted citation impact, top 11% of its field
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

16 citing papers in PubMed, 20 citations in OpenAlex.

  1. Trial
  2. Observational
  3. Article
  4. Article
  5. Article
  6. Review
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. 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 at 2 institutions in 2 countries.

Nikolai KleefeldtDepartment of Ophthalmology, University Hospital Würzburg, Würzburg, Germany.
Katharina BermondDepartment of Ophthalmology, University Hospital Würzburg, Würzburg, Germany.
Ioana-Sandra TarauDepartment of Ophthalmology, University Hospital Würzburg, Würzburg, Germany.
Jost HillenkampDepartment of Ophthalmology, University Hospital Würzburg, Würzburg, Germany.
Andreas BerlinDepartment of Ophthalmology, University Hospital Würzburg, Würzburg, Germany.
Kenneth R SloanDepartment of Computer Science, University of Alabama at Birmingham, Birmingham, AL, USA.
Thomas AchDepartment of Ophthalmology, University Hospital Würzburg, Würzburg, Germany.
Universitätsklinikum Würzburg · DEUniversity of Alabama at Birmingham · US

Funding

A hyperspectral approach to RPE fluorophores in AMDR01EY027948 · NEI · UNIVERSITY OF ALABAMA AT BIRMINGHAM · PI ACH, THOMAS, CURCIO, CHRISTINE A · 2017 to 2025
$3.8M
NEI NIH HHS R01 EY027948
6 · The paper itself

Abstract

Purpose: To use multimodal retinal images (including quantitative fundus autofluorescence [QAF]) for spectral-domain optical coherence tomography (SD-OCT)-based image registration and alignment. For each age decade of healthy adults, normative fine-grained QAF retinal maps are generated and advanced methods for QAF image analysis are applied. Methods: Multimodal retinal images were obtained from 103 healthy subjects (age 19-77 years; unremarkable retina/macula, age-appropriate clear optic media). Custom written FIJI plugins enabled: (1) determination of the fovea in SD-OCT and the edge of the optic disc in infrared (IR) images; (2) alignment and superimposition of multimodal retinal images based on foveal and optic disc position; (3) plotting of normative QAF retinal maps for each decade; and (4) comparison of individual retinas with normative retinas of different decades using newly introduced analysis patterns (QAF97, freehand tool). Results: SD-OCT based image registration enables easy image registration, alignment, and analysis of different modalities (QAF, IR, and SD-OCT here reported). In QAF, intensities significantly increase with age with two major inclines between the third/fourth and seventh/eighth decades. With aging, the parafoveal area of maximum QAF intensity slightly shifts from temporal-superior to temporal. Compared with standard QAF analysis, refined QAF analysis patterns reveal a more detailed analysis of QAF, especially in the diseased retina. Conclusions: Age-related QAF normative retinal maps can be used to directly compare and classify individual's QAF intensities. Advanced QAF analysis tools will further help to interpret autofluorescence changes in normal aging and in the diseased retina in a multimodal imaging setting. Translational Relevance: Advanced methods for QAF analysis link basic findings with clinical observations in normal aging and in the diseased macula.

Indexed as

Optic DiskTomography, Optical CoherenceAdultAgedFluorescein AngiographyHumansMiddle AgedOptical ImagingRetinaYoung Adultimage registrationoptical coherence tomographyquantitative fundus autofluorescencestandard retina

Identifiers

PMID32855849
PMCPMC7422829
OpenAlexW3039999777

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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.