Evidence map›Paper›PMID 28617921›Full record

ArticleJournal of biomedical optics2017

Optical coherence tomography angiography-based capillary velocimetry.

Ruikang K Wang, Qinqin Zhang, Yuandong Li, Shaozhen Song

Open access · goldAbstract read
In one paragraph

Article in Journal of biomedical optics, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 39 papers.

0numbers the graph read from it
0cells of the map it votes in
39citing papers in PubMed
3.1field-weighted citation impact, top 8% 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

39 citing papers in PubMed, 64 citations in OpenAlex.

  1. Biomedical optics express · 2026
    Article
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  5. Article
  6. Observational
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  13. The Impact of Carotid Endarterectomy on Choriocapillaris Perfusion.Investigative ophthalmology & visual science · 2023
    Observational
  14. Article
  15. Review
  16. Review
  17. Measuring capillary flow dynamics using interlaced two-photon volumetric scanning.Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism · 2023
    Article
  18. Article
  19. Article
  20. 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

4 authors at 1 institution in 1 country.

Ruikang K WangUniversity of Washington, Department of Bioengineering, Seattle, Washington, United StatesbUniversity of Washington, Department of Ophthalmology, Seattle, Washington, United States.
Qinqin ZhangUniversity of Washington, Department of Bioengineering, Seattle, Washington, United States.
Yuandong LiUniversity of Washington, Department of Bioengineering, Seattle, Washington, United States.
Shaozhen SongUniversity of Washington, Department of Bioengineering, Seattle, Washington, United States.
University of Washington · US

Funding

OPTICAL MICROANGIOGRAHY OF CEREBROVASCULAR PERFUSIONR01HL093140 · NHLBI · UNIVERSITY OF WASHINGTON · PI WANG, RUIKANG · 2008 to 2017
$4.2M
NON-INVASIVE REAL-TIME LABEL-FREE 3D IMAGING OF RETINAL MICROCIRCULATIONR01EY024158 · NEI · UNIVERSITY OF WASHINGTON · PI WANG, RUIKANG · 2014 to 2017
$1.7M
NEI NIH HHS R01 EY024158NHLBI NIH HHS R01 HL093140
6 · The paper itself

Abstract

Challenge persists in the field of optical coherence tomography (OCT) when it is required to quantify capillary blood flow within tissue beds in vivo. We propose a useful approach to statistically estimate the mean capillary flow velocity using a model-based statistical method of eigendecomposition (ED) analysis of the complex OCT signals obtained with the OCT angiography (OCTA) scanning protocol. ED-based analysis is achieved by the covariance matrix of the ensemble complex OCT signals, upon which the eigenvalues and eigenvectors that represent the subsets of the signal makeup are calculated. From this analysis, the signals due to moving particles can be isolated by employing an adaptive regression filter to remove the eigencomponents that represent static tissue signals. The mean frequency (MF) of moving particles can be estimated by the first lag-one autocorrelation of the corresponding eigenvectors. Three important parameters are introduced, including the blood flow signal power representing the presence of blood flow (i.e., OCTA signals), the MF indicating the mean velocity of blood flow, and the frequency bandwidth describing the temporal flow heterogeneity within a scanned tissue volume. The proposed approach is tested using scattering phantoms, in which microfluidic channels are used to simulate the functional capillary vessels that are perfused with the scattering intralipid solution. The results indicate a linear relationship between the MF and mean flow velocity. In vivo animal experiments are also conducted by imaging mouse brain with distal middle cerebral artery ligation to test the capability of the method to image the changes in capillary flows in response to an ischemic insult, demonstrating the practical usefulness of the proposed method for providing important quantifiable information about capillary tissue beds in the investigations of neurological conditions in vivo.

Indexed as

Blood Flow VelocityTomography, Optical CoherenceAngiographyAnimalsCapillariesMiceRheology

Identifiers

PMID28617921
PMCPMC5472241
OpenAlexW2626704232

What OpenQuestion holds

Textmetadata
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.