Evidence map›Paper›PMID 32557002›Full record

ArticleLasers in medical science2021

Improving imaging depth by dynamic laser speckle imaging and topical optical clearing for in vivo blood flow monitoring.

Xu Sang, Dong Li, Bin Chen

Abstract read
PubMed Publisher
In one paragraph

Article in Lasers in medical science, 2021. 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
1.3field-weighted citation impact, top 20% 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

6 citing papers in PubMed, 15 citations in OpenAlex.

  1. Article
  2. Article
  3. Journal of biomedical optics · 2023
    Review
  4. Article
  5. 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

3 authors at 1 institution in 1 country.

Xu SangState Key Laboratory of Multiphase Flow in Power Engineering, Xi'an Jiaotong University, Xi'an, 710049, Shaanxi, China.
Dong LiState Key Laboratory of Multiphase Flow in Power Engineering, Xi'an Jiaotong University, Xi'an, 710049, Shaanxi, China.
Bin ChenState Key Laboratory of Multiphase Flow in Power Engineering, Xi'an Jiaotong University, Xi'an, 710049, Shaanxi, China. chenbin@mail.xjtu.edu.cn.
Xi'an Jiaotong University · CN

Funding

National Natural Science Foundation of China 51727811
6 · The paper itself

Abstract

Laser speckle contrast imaging (LSI) is a promising non-invasive full-field blood flow monitoring technique. However, it is still far from clinic practice due to insufficient contrast-to-noise ratio (CNR) and limited detection depth. In this study, an in vivo laser speckle imaging visualization system was constructed to observe the blood circulation on a dorsal skin. A dynamic laser speckle imaging (dLSI) scheme, other than traditional laser speckle contrast analysis method, was applied to separate the dynamic light scattering from the static one to increase the image CNR. Based on the theoretical optimization for dLSI, at least two pixels are required for speckle pattern sampling and a spatial window size of 7 × 7 was optimal to balance the spatial resolution and statistical accuracy. The in vivo experiment observation shows that the CNR is improved 8.4 times by dLSI. The blood vessels were more pronounced, and more capillaries can be observed than in traditional laser speckle contrast images. Topical optical clearing technique by thiazone was combined with dLSI to increase the sampling depth from 700 to 1000 μm.

Indexed as

Laser Speckle Contrast ImagingRegional Blood FlowAlgorithmsAnimalsComputer SimulationFemaleHemodynamicsNumerical Analysis, Computer-AssistedOptical ImagingPhantoms, ImagingRatsRats, Sprague-DawleySkinTime FactorsDynamic laser speckle imagingHemodynamicsLaser speckle contrast imagingTopical optical clearing

Identifiers

PMID32557002
OpenAlexW3036861637

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.