Evidence map›Paper›PMID 30834722›Full record

ArticleJournal of biomedical optics2019

Optimized depth-resolved estimation to measure optical attenuation coefficients from optical coherence tomography and its application in cerebral damage determination.

Jian Liu, Ning Ding, Yao Yu, Xincheng Yuan, Shuzhuo Luo, Jingmin Luan, Yuqian Zhao, Yi Wang, Zhenhe Ma

Abstract read
In one paragraph

Article in Journal of biomedical optics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers.

0numbers the graph read from it
0cells of the map it votes in
30citing 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

30 citing papers in PubMed.

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  15. Neurophotonics · 2023
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  18. Observational
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  20. Differentiation of otitis media-causing bacteria and biofilmsFrontiers in cellular and infection microbiology · 2022
    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

9 authors.

Jian LiuNortheastern Univ. at Qinhuangdao, China.
Ning DingNortheastern Univ., China.
Yao YuNortheastern Univ. at Qinhuangdao, China.
Xincheng YuanUniv. of Michigan, United States.
Shuzhuo LuoNortheastern Univ., China.
Jingmin LuanNortheastern Univ. at Qinhuangdao, China.
Yuqian ZhaoNortheastern Univ. at Qinhuangdao, China.
Yi WangNortheastern Univ. at Qinhuangdao, China.
Zhenhe MaNortheastern Univ. at Qinhuangdao, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The optical attenuation coefficient (OAC) reflects the optical properties of various tissues or tissues of the same type under different physiological conditions. Quantitative measurement of OAC from optical coherence tomography (OCT) signals can provide additional information and can increase the potential for OCT applications. We present an optimized depth-resolved estimation (ODRE) method that derives a precise mapping between the measured OCT signal and the OAC. In contrast to previous depth-resolved estimation (DRE) methods, the optimized method can estimate the OAC in any depth range and ignore whether the light is completely attenuated. Numerical simulations and phantom experiments are used to verify its validity, and this method is applied to detect cerebral damage. In combination with OCT angiography, real-time observation of the change of blood perfusion and the degree of cerebral damage in mice with focal cerebral ischemia provides important information to help us understand the temporal relationship between brain damage and ischemia.

Indexed as

AlgorithmsAnimalsBrainBrain IschemiaCerebral AngiographyComputer SimulationImage Processing, Computer-AssistedMicePhantoms, ImagingTomography, Optical Coherencecerebral ischemiaoptical attenuation coefficientoptical coherence tomographyoptimized depth-resolved estimation

Identifiers

PMID30834722
PMCPMC6975193

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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.