Evidence map›Paper›PMID 36273250›Full record

ArticleJournal of biomedical optics2022

Highly accurate, automated quantification of 2D/3D orientation for cerebrovasculature using window optimizing method.

Jia Meng, Lingxi Zhou, Shuhao Qian, Chuncheng Wang, Zhe Feng, Shenyi Jiang, Rushan Jiang, Zhihua Ding, Jun Qian, Shuangmu Zhuo and 1 more

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Journal of biomedical optics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.7field-weighted citation impact, top 31% 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

1 citing paper in PubMed, 5 citations in OpenAlex.

  1. Review
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

11 authors at 3 institutions in 1 country.

Jia MengZhejiang University, College of Optical Science and Engineering, International Research Center for Advanced Photonics, State Key Laboratory of Modern Optical Instrumentation, Hangzhou, China, China.
Lingxi ZhouZhejiang University, College of Optical Science and Engineering, International Research Center for Advanced Photonics, State Key Laboratory of Modern Optical Instrumentation, Hangzhou, China, China.
Shuhao QianZhejiang University, College of Optical Science and Engineering, International Research Center for Advanced Photonics, State Key Laboratory of Modern Optical Instrumentation, Hangzhou, China, China.
Chuncheng WangZhejiang University, College of Optical Science and Engineering, International Research Center for Advanced Photonics, State Key Laboratory of Modern Optical Instrumentation, Hangzhou, China, China.
Zhe FengZhejiang University, College of Optical Science and Engineering, International Research Center for Advanced Photonics, State Key Laboratory of Modern Optical Instrumentation, Hangzhou, China, China.
Shenyi JiangZhejiang University, College of Optical Science and Engineering, International Research Center for Advanced Photonics, State Key Laboratory of Modern Optical Instrumentation, Hangzhou, China, China.
Rushan JiangZhejiang University, College of Optical Science and Engineering, International Research Center for Advanced Photonics, State Key Laboratory of Modern Optical Instrumentation, Hangzhou, China, China.
Zhihua DingZhejiang University, College of Optical Science and Engineering, International Research Center for Advanced Photonics, State Key Laboratory of Modern Optical Instrumentation, Hangzhou, China, China.
Jun QianZhejiang University, College of Optical Science and Engineering, International Research Center for Advanced Photonics, State Key Laboratory of Modern Optical Instrumentation, Hangzhou, China, China.
Shuangmu ZhuoJimei University, School of Science, Xiamen, China, China.
Zhiyi LiuZhejiang University, College of Optical Science and Engineering, International Research Center for Advanced Photonics, State Key Laboratory of Modern Optical Instrumentation, Hangzhou, China, China.
State Key Laboratory of Modern Optical InstrumentsZhejiang University · CNJimei University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Significance: Deep-imaging of cerebral vessels and accurate organizational characterization are vital to understanding the relationship between tissue structure and function. Aim: We aim at large-depth imaging of the mouse brain vessels based on aggregation-induced emission luminogens (AIEgens), and we create a new algorithm to characterize the spatial orientation adaptively with superior accuracy. Approach: Assisted by AIEgens with near-infrared-II excitation, three-photon fluorescence (3PF) images of large-depth cerebral blood vessels are captured. A window optimizing (WO) method is developed for highly accurate, automated 2D/3D orientation determination. The application of this system is demonstrated by establishing the orientational architecture of mouse cerebrovasculature down to the millimeter-level depth. Results: The WO method is proved to have significantly higher accuracy in both 2D and 3D cases than the method with a fixed window size. Depth- and diameter-dependent orientation information is acquired based on in vivo 3PF imaging and the WO analysis of cerebral vessel images with a penetration depth of 800 μm in mice. Conclusions: We built an imaging and analysis system for cerebrovasculature that is conducive to applications in neuroscience and clinical fields.

Indexed as

Diagnostic ImagingPhotonsAlgorithmsAnimalsBrainFluorescenceMiceaggregation-induced emissioncerebrovasculatureorientationwindow optimizing

Identifiers

PMID36273250
PMCPMC9587757
OpenAlexW4307229072

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.