Evidence map›Paper›PMID 37791271›Full record

ArticleBiomedical optics express2023

Measurements of slow tissue dynamics with short-separation speckle contrast optical spectroscopy.

Bingxue Liu, Shashwat Shah, Gülce Küreli, Anna Devor, David A Boas, Xiaojun Cheng

Abstract read
In one paragraph

Article in Biomedical optics express, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. 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

6 authors.

Bingxue LiuNeurophotonics Center, Boston University, Boston, Massachusetts 02215, USA.
Shashwat ShahNeurophotonics Center, Boston University, Boston, Massachusetts 02215, USA.
Gülce KüreliNeurophotonics Center, Boston University, Boston, Massachusetts 02215, USA.
Anna DevorNeurophotonics Center, Boston University, Boston, Massachusetts 02215, USA.
David A BoasNeurophotonics Center, Boston University, Boston, Massachusetts 02215, USA.
Xiaojun ChengNeurophotonics Center, Boston University, Boston, Massachusetts 02215, USA.ORCID https://orcid.org/0000-0002-3568-0603

Funding

Project 4U19NS123717 · NINDS · BOSTON UNIVERSITY (CHARLES RIVER CAMPUS) · PI LINNINGER, ANDREAS A · 2021 to 2025
$13.4M
Neurophotonic Advances for Mechanistic Investigation of the Role of Capillary Dysfunction in Stroke RecoveryR01NS127156 · NINDS · BOSTON UNIVERSITY (CHARLES RIVER CAMPUS) · PI David A Boas · 2022 to 2026
$3.3M
The impact of microvascular (dys)regulation on cerebral flow and oxygen heterogeneityR01NS108472 · NINDS · BOSTON UNIVERSITY (CHARLES RIVER CAMPUS) · PI BOAS, DAVID A, SCHAFFER, CHRIS B · 2018 to 2022
$3.2M
NINDS NIH HHS R01 NS108472NINDS NIH HHS R01 NS127156NINDS NIH HHS U19 NS123717
6 · The paper itself

Abstract

Laser speckle contrast imaging (LSCI) measures 2D maps of cerebral blood flow (CBF) in small animal brains such as mice. The contrast measured in LSCI also includes the static and slow-varying components that contain information about brain tissue dynamics. But these components are less studied as compared to the fast dynamics of CBF. In traditional wide-field LSCI, the contrast measured in the tissue is largely contaminated by neighboring blood vessels, which reduces the sensitivity to these static and slow components. Our goal is to enhance the sensitivity of the contrast to static and slow tissue dynamics and test models to quantify the characteristics of these components. To achieve this, we have developed a short-separation speckle contrast optical spectroscopy (ss-SCOS) system by implementing point illumination and point detection using multi-mode fiber arrays to enhance the static and slow components in speckle contrast measurements as compared to traditional wide-field LSCI (WF-LSCI). We observed larger fractions of the static and slow components when measured in the tissue using ss-SCOS than in traditional LSCI for the same animal and region of interest. We have also established models to obtain the fractions of the static and slow components and quantify the decorrelation time constants of the intensity auto-correlation function for both fast blood flow and slower tissue dynamics. Using ss-SCOS, we demonstrate the variations of fast and slow brain dynamics in animals before and post-stroke, as well as within an hour post-euthanasia. This technique establishes the foundation to measure brain tissue dynamics other than CBF, such as intracellular motility.

Identifiers

PMID37791271
PMCPMC10545176

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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.