Evidence map›Paper›PMID 34221679›Full record

ArticleBiomedical optics express2021

Choosing a model for laser speckle contrast imaging.

Chang Liu, Kıvılcım Kılıç, Sefik Evren Erdener, David A Boas, Dmitry D Postnov

Abstract read
In one paragraph

Article in Biomedical optics express, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 42 papers.

0numbers the graph read from it
0cells of the map it votes in
42citing 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

42 citing papers in PubMed.

  1. Preclinical in-vivo cerebrovascular imaging in rodent models: Methods and applications in Alzheimer's disease.Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism · 2026
    Review
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  4. Mapping fast tissue dynamics with long camera exposures via intensity modulation.Proceedings of the National Academy of Sciences of the United States of America · 2026
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  19. Laser speckle imaging of the hippocampus.Biomedical optics express · 2024
    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

5 authors.

Chang LiuDepartment of Biomedical Engineering, Boston University, Massachusetts 02215, USA.ORCID https://orcid.org/0000-0001-7661-5456
Kıvılcım KılıçNeurophotonics Center, Boston University, Massachusetts 02215, USA.
Sefik Evren ErdenerNeurophotonics Center, Boston University, Massachusetts 02215, USA.
David A BoasDepartment of Biomedical Engineering, Boston University, Massachusetts 02215, USA.
Dmitry D PostnovNeurophotonics Center, Boston University, Massachusetts 02215, USA.ORCID https://orcid.org/0000-0002-9708-8453

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Laser speckle contrast imaging (LSCI) is a real-time full-field non-invasive technique, which is broadly applied to visualize blood flow in biomedical applications. In its foundation is the link between the speckle contrast and dynamics of light scattering particles-erythrocytes. The mathematical form describing this relationship, which is critical for accurate blood flow estimation, depends on the sample's light-scattering properties. However, in biological applications, these properties are often unknown, thus requiring assumptions to be made to perform LSCI analysis. Here, we review the most critical assumptions in the LSCI theory and simulate how they affect blood flow estimation accuracy. We show that the most commonly applied model can severely underestimate the flow change, particularly when imaging brain parenchyma or other capillary perfused tissue (e.g. skin) under ischemic conditions. Based on these observations and guided by the recent experimental results, we propose an alternative model that allows measuring blood flow changes with higher accuracy.

Identifiers

PMID34221679
PMCPMC8221943

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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.